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					ASSIGNMENT



Course Code                     :        MS-95

Course Title                    :        Research Methodology for Management Decisions
Assignment No.                  :        95/TMA /SEM-I/2011

Coverage                        :        All Blocks

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Note: Answer all the questions and send them to the Coordinator of the Study Centre you are attached
        with.
1.      What is problem definition in research process? Discuss the various steps of research process
        with an illustrative example from management.


Solution : Research is the function that links the consumer, customer, and public to the marketer through
information. This information is used to identify and define marketing opportunities and problems; to
generate, refine, and evaluate marketing actions; to monitor marketing performance; and to improve
understanding of the marketing process. Marketing research specifies the information, manages and
implements the data-collection process, analyzes the results, and communicates the findings and their
implications. Marketing research is concerned with the application of theories, problem-solving methods,
and techniques to identify and solve problems in marketing. In order to offset unpredictable consumer
behavior, companies invest in market research.


Increased customer focus, demands for resource productivity, and increased domestic and international
competition has prompted an increased emphasis on marketing research. Managers cannot always wait for
information to arrive in bits and pieces from marketing departments. They often require formal studies of
specific situations. For example, Dell Computer might want to know a demographic breakdown of how
many and what kinds of people or companies will purchase a new model in its personal computer line. In
such situations, the marketing department may not be able to provide from existing knowledge the
detailed information needed, and managers normally do not have the skill or time to obtain the
information on their own. This formal study, whether performed internally or externally, is called
marketing research.


The marketing research process consists of four steps: defining the problem and research objectives,
developing the research plan, implementing the research plan, and interpreting and reporting the findings.


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DEFINING THE OBJECTIVES


The marketing manager and the researcher must work closely together to define the problem carefully and
agree on the research objectives. The manager best understands the decision for which information is
needed; the researcher best understands marketing research and how to obtain the information.


Managers must know enough about marketing research to help in the planning and to interpret research
results. Managers who know little about the importance of research may obtain irrelevant information or
accept inaccurate conclusions. Experienced marketing researchers who understand the manager's problem
should also be involved at this stage. The researcher must be able to help the manager define the problem
and to suggest ways that research can help the manager make better decisions.


Defining the problem and research objectives is often the hardest step in the research process. The
manager may know that something is wrong without knowing the specific causes. For example, managers
of a retail clothing store chain decided that falling sales were caused by poor floor set-up and incorrect
product positioning. However, research concluded that neither problem was the cause. It turned out that
the store had hired sales persons who weren't properly trained in providing good customer service.
Careful problem definition would have avoided the cost and delay of research and would have suggested
research on the real problem.


When the problem has been defined, the manager and researcher must set the research objectives. A
marketing research project might have one of three types of objectives. Sometimes the objective is
exploratory—to gather preliminary information that will help define the problem and suggest hypotheses.
Sometimes the objective is descriptive—to describe things such as the market potential for a product or
the demographics and attitudes of consumers who buy the product. Sometimes the objective is casual—to
test hypotheses about cause-and-effect relationships.


DEVELOPING THE RESEARCH PLAN


The second step of the marketing research process calls for determining the information needed,
developing a plan for gathering it efficiently, and presenting the plan to marketing management. The plan
outlines sources of secondary data and spells out the specific research approaches, contact methods,
sampling plans, and instruments that researchers will use to gather primary data.




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A marketing researcher can gather secondary data, primary data, or both. Primary data consists of
information collected for the specific purpose at hand. Secondary data consists of information that already
exists somewhere, having been collected for another purpose. Sources of secondary data include internal
sources such as profit and loss statements, balance sheets, sales figures, and inventory records; and
external sources such as government publications, periodicals, books, and commercial data. Primary data
collection requires more extensive research, more time, and more money. Secondary sources can
sometimes provide information that is not directly available or would be too expensive to collect.


Secondary data also present problems. The needed information may not exist. Researchers can rarely
obtain all the data they need from secondary sources. The researcher must evaluate secondary information
carefully to make certain of its relevance (fits research project needs), accuracy (reliably collected and
reported), currency (up to date enough for current decisions), and impartiality (objectively collected and
reported). Researchers must also understand how secondary sources define basic terms and concepts, as
different sources often use the same terms but mean slightly different things, or they attempt to measure
the same thing but go about it in different ways. Either way, the result can be that statistics found in
secondary sources may not be as accurate or as relevant as they appear on the surface.


RESEARCH APPROACHES


Observational research is the gathering of primary data by observing relevant people, actions, and
situations. Observational research can be used to obtain information that people are unwilling or unable to
provide. In some cases, observation may be the only way to obtain the needed information.


Survey research is the approach best suited for gathering descriptive information. A company that wants
to know about people's knowledge, attitudes, preferences, or buying behavior can often find out by asking
them directly. Survey research is the most widely used method for primary data collection, and it is often
the only method used in a research study. The major advantage of survey research is its flexibility. It can
be used to obtain many different kinds of information in many different marketing situations. In the early
and mid-1980s, some cola companies created a taste test against their competitors. This is an example of
survey research. Participants were allowed to taste different cola brands without knowing which was
which. The participant then decided which brand was preferred.


Whereas observation is best suited for exploratory research and surveys for descriptive research,
experimental research is best suited for gathering causal information. Experiments involve selecting


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matched groups of subjects, giving them different treatments, controlling unrelated factors, and checking
for differences in group responses. Thus, experimental research tries to explain cause-and-effect
relationships.


RESEARCH CONTACT METHODS


Research may be collected by mail, telephone, e-mail, fax, or personal interview. Mail questionnaires can
be used to collect large amounts of information at a low cost per respondent. Respondents may give more
honest answers to more personal questions on a mail questionnaire than to an unknown interviewer in
person or over the phone. However, mail questionnaires lack flexibility in that they require simply
worded questions. They can also take a long time to complete, and the response rate—the number of
people returning completed questionnaires—is often very low.


Telephone interviewing is the best method for gathering information quickly, and it provides greater
flexibility than mail questionnaires. Interviewers can explain questions that are not understood. Telephone
interviewing also allows greater sample control. Response rates tend to be higher than with mail
questionnaires. But telephone interviewing also has its drawbacks. The cost per respondent is higher than
with mail questionnaires, people may regard a phone call as more of an inconvenience or an intrusion,
and they may not want to discuss personal questions with an interviewer. In the latter part of the 1990s,
laws were also passed to guard against the invasion of privacy. If a person wishes to be taken off a
solicitation or interview list, companies can be sued if they persist in calling.


Personal interviewing consists of inviting several people to talk with a trained interviewer about a
company's products or services. The interviewer needs objectivity, knowledge of the subject and industry,
and some understanding of group and consumer behavior. Personal interviewing is quite flexible and can
be used to collect large amounts of information. Trained interviewers can hold a respondent's attention for
a long time and can explain difficult questions. They can guide interviews, explore issues, and probe as
the situation requires. The main drawbacks of personal interviewing are costs and sampling problems.
Personal interviews may cost three to four times as much as telephone interviews.


SAMPLING PLAN


Marketing researchers usually draw conclusions about large groups of consumers by studying a relatively
small sample of the total consumer population. A sample is a segment of the population selected to


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represent the population as a whole. Ideally, the sample should be representative so that the researcher can
make accurate estimates of the thoughts and behaviors of the larger population. If the sample is not
representative, it may lead the company to draw the wrong conclusions and misuse its resources.


The marketing researcher must design a sampling plan, which calls for three decisions:


    1. Sampling unit—determining who is to be surveyed. The marketing researcher must define the
        target population that will be sampled. If a company wants feedback on a new basketball shoe, it
        would be wise to target active players and even professional players.
    2. Sample size—determining the number of people to be surveyed. Large samples give more
        reliable results than small samples. Samples of less than 1 percent of a population can often
        provide good reliability, given a credible sampling procedure. Most commercial samples consist
        of between several hundred and several thousand respondents.
    3. Sampling procedure—determining how the respondents should be chosen. To obtain a
        representative sample, a probability (random) sampling of the population should be drawn. This
        is a means of determining who is reached by the survey to ensure they are indeed a valid cross-
        section of the sampling unit. Choosing passersby on a street corner, for example, would not
        produce a random sample, whereas allowing a computer to pick names randomly from a relevant
        calling list probably would (depending on how the list was compiled). Probability sampling
        allows the calculation of confidence limits for sampling error.


RESEARCH INSTRUMENTS


In collecting primary data, marketing researchers have a choice of two main research instruments—the
questionnaire and mechanical devices. The questionnaire is by far the most common instrument. A
questionnaire consists of a set of questions presented to a respondent for his or her answers. In preparing a
questionnaire, the marketing researcher must decide what questions to ask, the form of the questions, the
wording of the questions, and the ordering of the questions. Each question should be checked to see that it
contributes to the research objectives.


Although questionnaires are the most common research instrument, mechanical instruments are also used.
Two examples of mechanical instruments are people meters and supermarket scanners. These techniques
are not widely used because they tend to be expensive, require unrealistic advertising exposure
conditions, and are hard to interpret.


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COLLECTING THE INFORMATION


The researcher must now collect the data. This phase is generally the most expensive and the most liable
to error. In the case of surveys, four major problems arise. Some respondents will not be at home and will
have to be replaced. Other respondents will refuse to cooperate. Still others will give biased or dishonest
answers. Finally, some interviewers will occasionally be biased or dishonest.


CHARACTERISTICS OF GOOD MARKETING RESEARCH


Following are the characteristics of good marketing research


    1. Scientific method. Effective marketing research uses the principles of the scientific method:
        careful observation, formulation of hypotheses, prediction, and testing.
    2. Research creativity. At its best, marketing research develops innovative ways to solve a problem.
    3. Multiple methods. Competent marketing researchers shy away from over-reliance on any one
        method, preferring to adapt the method to the problem rather than the other way around. They
        also recognize the desirability of gathering information from multiple sources to give greater
        confidence.
    4. Interdependence of models and data. Competent marketing researchers recognize that the facts
        derive their meaning from models of the problem. These models guide the type of information
        sought and therefore should be made as explicit as possible.
    5. Value and cost of information. Competent marketing researchers show concern for estimating the
        value of information against its cost. Value/cost evaluation helps the marketing research
        department determine which research projects to conduct, which research designs to use, and
        whether to gather more information after the initial results are in. Research costs are typically
        easy to quantify, while the value is harder to anticipate. The value depends on the reliability and
        validity of the research findings and management's willingness to accept and act on its findings.
        In general, the most valuable information tends to cost the most because it requires more
        intensive methods, but of course it is easy to spend a great deal of money on poorly conceived
        research.
    6. Healthy skepticism. Competent marketing researchers will show a healthy skepticism toward
        assumptions made by managers about how the market works.
    7. Ethical marketing. Most marketing research benefits both the sponsoring company and its
        consumers. Through marketing research, companies learn more about consumers' needs, and are

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        able to supply more satisfying products and services. However, the misuse of marketing research
        can also harm or annoy consumers. There are professional ethical standards guiding the proper
        conduct of research.


PRESENTING THE RESEARCH PLAN


The last step in market research is the presentation of a formal plan. At this stage, the marketing
researcher should summarize the plan in a written proposal to management. A written proposal is
especially important when the research project will be large and complex or when an outside firm carries
it out. The proposal should cover the management problems addressed and the research objectives, the
information to be obtained, the sources of secondary information or methods for collecting primary data,
and the way the results will help management decision making. A written research plan or proposal
makes sure that the marketing manager and researchers have considered all the important aspect of the
research and that they agree on why and how the research will be done.


MANAGEMENT'S USE OF MARKETING RESEARCH


In spite of the rapid growth of marketing research, many companies still fail to use it sufficiently or
correctly. Several factors can stand in the way of its greater utilization.


    1. A narrow conception of marketing research. Many managers see marketing research as only a
        fact-finding operation. The marketing researcher is supposed to design a questionnaire, choose a
        sample conduct interviews, and report results, often without being given a careful definition of
        the problem or of the decision alternatives facing management. As a result, some fact finding fails
        to be useful. This reinforces management's idea of the limited usefulness of some marketing
        research.
    2. Uneven caliber of marketing researchers. Some managers view marketing research as little better
        than a clerical activity and reward it as such. Poorly qualified marketing researchers are hired,
        and their weak training and deficient creativity lead to unimpressive results. The disappointing
        results reinforce management's prejudice against expecting too much from marketing research.
        Management continues to pay low salaries, perpetuating the basic difficulty.
    3. Late and occasional erroneous findings by marketing research. Managers want quick results that
        are accurate and conclusive. But good marketing research takes time and money. If they can't
        perceive the difference between quality and shoddy research, managers become disappointed, and


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        they lower their opinion of the value of marketing research. This is especially a problem in
        conducting marketing research in foreign countries.
    4. Intellectual differences. Intellectual divergences between the mental styles of line managers and
        marketing researchers often get in the way of productive relationships. The marketing researcher's
        report may seem abstract, complicated, and tentative, while the line manager wants concreteness,
        simplicity, and certainty. Yet in the more progressive companies, marketing researchers are
        increasingly being included as members of the product management team, and their influence on
        marketing strategy in growing.


RESEARCH METHODS AND PROCESSES

In any organization, managers at all levels need accurate and timely information for managerial decision
making. Whether the decisions made are at technical, tactical, or strategic levels, good, accurate, and
timely information always leads to a better decision. Gathering of information is done through a sound
and scientific research process. Each year organizations spend enormous amounts of money for research
and development in order to maintain their competitive edge. Accurate information obtained through
research leads to enormous benefits.

APPLIED VERSUS PURE RESEARCH

Research can be defined as scientifically and methodically delving into the unknown in order to provide
information for solving problems. The heart of this definition is the concept of problem solving. Both
applied and pure (also known as basic) research attempt to solve problems. In applied research, the
researcher attempts to solve a known problem and find answers to specific questions. In other words, the
emphasis of applied research is on practical problem solving. For instance, when a paper recycling
company wants to determine whether or not their recycled papers meet the required specification as to the
thickness of the paper across the roll, they might design a systematic procedure for answering this specific
question. The research in such a situation represents applied research. Another example of applied
research might be that of prediction. As an example, consider a trucking company that is interested in
predicting the tonnage of material shipped in the next quarter. The practical problem is predicting the
tonnage and determining which variables are good predictors of tonnage for the next quarter.

Applied research can help make a decision about the following, including a variety of other business and
management decisions:

       pricing a new product
       where to locate a new retail store
       how many employees to hire

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       how many products to offer
       what to pay employees

Applied research can be used to collect information about markets, competitors, and customers. For
example, research can help pinpoint the optimal business location and the size of markets. It can also be
used to monitor competitive actions. Customer research determines customer loyalty, customer
satisfaction, and customer preferences.

On the other hand, pure, or basic, research does not necessarily try to answer specific questions or solve
specific problems. Pure or basic research is done in order to expand knowledge and probe into the
unknown. For example, when a researcher is interested in determining how employee demographics and
tenure on the job relate to preference for flexible work schedules may represent pure research. Both pure
and applied research deals with problem definition and problem solving. Most basic research is conducted
by professors in academic institutions (i.e. colleges and universities), by the government, or by consulting
firms. Few business organizations will engage in pure research related to business problems. However,
understanding the process and methods used for both applied and basic research are important to
interpreting research results.

RESEARCH PROCESS

Any research involves several chronological steps, but that does not mean each step must be completed
before the next step is undertaken. Furthermore, the process of research is dynamic and the process may
change as the research progresses. The steps involved in most research endeavors are shown in Figure 1.




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Figure 1
The Research Process

THE RESEARCH QUESTION

Managers' needs for information are the primary source of problem definition and the research question.
Managers need information to make educated decisions arising from unanticipated as well as planned
changes. As such, managers must select between different alternatives and thus require information about
the organization and its environment. The question to be answered or the problem to be solved must first
be clearly defined. Questions to be answered could be very specific or extremely broad. The more specific
the questions, the easier it will be to answer the research questions. There might be hypotheses that could
be tested scientifically. Once the questions to be answered are clearly defined then the value of the
research must be assessed. Clearly, if the costs of performing the research project exceed the value that
the research will provide, then the project should not be continued.

THE RESEARCH PROPOSAL

Research endeavors require a proposal that explains the problem to be address and the procedure by
which the questions will be answered. The researcher's proposal tells the managers what they should
expect from the research. It is a contract between the managers and the researcher. For instance, if a
company wants to know the degree to which its new incentive program is effective in improving
employee performance, then the consultant or employee conducting the research will create a proposal
that indicates to that company how the question will be addressed and what specific information the
company will have at the end of the research process. The proposal may indicate, for example, that the
research will indicate the level of satisfaction of employees with the new incentive plan, the increased
firm performance with the plan, and the individual increases in performance (as measured by managers)
with the incentive plan. The purpose of the research proposal is to effectively guide the researchers in
their development of the research design and data collection to answer the specific research questions.

RESEARCH DESIGN

Once the proposal is approved, the researcher has a foundation for development of the research design.
The plan for conducting the research is the research design. There are two general forms of research
design, namely non-experimental (ex-post-facto) and experimental. In a non-experimental design, the
researcher does not control or alter any of the independent variables. The researcher merely studies
existing situations, variables, and the interrelation among variables and reports the results of his or her
findings. The two major non-experimental designs are field studies and surveys. Field studies combine
literature review and possibly analysis of some case studies. For example, if one is interested in
determining the effectiveness of total quality management (TQM), there will be a thorough literature
search on the topic as well as a study of the firms that have applied TQM and have been successful. A

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literature review means that a researcher identifies previous writings and research on a topic, summarizes
the current knowledge on the topic, and assesses the value of that prior research on the current problem.
On the other hand, surveys deal with the formulation of a questionnaire (survey instrument) by which one
can measure the magnitude of the desired variables as well as the interrelation among the variables. Non-
experimental designs are primarily exploratory in nature and provide descriptive measures and can also be
used for predictive purposes.

There are two broad categories of experimental designs: field and laboratory. In both field experiments
and laboratory experiments, the researcher controls and may alter and introduce some variables in order to
determine the effect of a given variable. Field experiments are done in a natural setting, whereas
laboratory experiments are undertaken in a simulated setting. Studies on the effectiveness of different
configurations of teams and their level of effectiveness can be undertaken in both field and office settings.
In an office setting, a researcher might organize workplace teams, using different criteria to establish
each, then measure the success of their group interactions and their productivity on real work tasks. This
would be a natural setting, except for the way in which teams were organized. Team composition could
also be studied in a laboratory in which the researchers had complete control over more variables. To
study team effectiveness in a laboratory setting, individuals would be placed in teams using different
criteria, then asked to perform a series of tasks specially designed to measure team interactions and
performance. This laboratory setting would allow the researcher more control, because the types of
individuals involved could be chosen, rather than using only the employees available in a field setting; by
designing tasks specific to the study, rather than using existing work tasks; and by having more ability to
watch and measure team performance without hindering organizational performance.

DATA COLLECTION

Data collection is the process of gathering the specific information used to answer the research questions.
There are a number of issues associated with data collection, including the use of primary or secondary
data, survey design, sampling, survey administration, and increasing response rates.

PRIMARY DATA AND SECONDARY DATA.

Data can be primary or secondary, and whether one or both are used, and which is used, depends largely
on the research question and the availability of these data sources. Secondary data refer to data gathered
by others or from other studies. Secondary data is generally less costly and less time consuming than
gathering primary data, typically is accumulated before primary data is gathered, and may even help
determine the course by which primary data is pursued. An example of secondary data is if a company
uses data from the U.S. Census or data collected for another organizational activity (e.g., performance
information for individuals from the company's annual performance appraisal). While secondary data can
be used for background information about specific research, it may also answer some specific research


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questions. However, because secondary data was collected for another purpose, it may not adequately
address the new research question. In today's world of rapidly growing information technologies,
secondary data are available from numerous sources. A researcher should explore the existing data before
starting the research process, since there are datasets for many different types of information currently
available. There are abundant data available in literature, company records, government publications,
trade associations, and through the Internet.

Primary data is that which is collected by the researcher to address the current research question. Types of
primary data include subject demographics, lifestyle characteristics, attitudes, knowledge, intentions,
motivations, and behavior. Demographic data includes statistics regarding populations, such as age, sex,
income, level of education, and so forth. Lifestyle characteristics describe a respondent's activities,
interests, and opinions. Attitudes refer to views and opinions about things, events, or ideas. Knowledge is
the degree to which respondents are aware of these things, events, or ideas. Intentions generally refer to a
respondent's planned future behavior. Motivations describe the reasons behind a respondent's behavior.
Behavior is related to what respondents do.

Primary data can be collected in the field or the laboratory through communication and observation.
Communication generally requires the direct questioning of respondents via a paper-and-pencil survey
(i.e., questionnaire) or telephone survey. Observation involves the direct recording of respondent
behavior. Surveys are probably the most common design in business research. For instance, if one is
interested in determining the success of TQM, a survey can be designed that encompasses questions
regarding elements of success, strengths, weaknesses, and other questions dealing with TQM. Then the
survey can be sent to companies that have been successful in implementing TQM. The survey results
could shed light on many aspects of TQM.

SURVEY DESIGN.

Survey design is of major importance, because is a survey is poorly designed, it will not provide the
researchers with the data that addresses the research question. Survey questions, called items, must be
properly chosen to in order to elicit appropriate respondent answers. The steps involved include
determining the information that will be sought, the type of questionnaire, the method of administration,
the content of individual questions, the form of response to each question, the wording of each question,
the sequence of questions, the physical characteristics of the questionnaire, and, finally, pre-testing the
questionnaire.

Some items for certain areas of interest already exist. For instance, there are existing surveys that measure
employees' satisfaction with pay and benefits. If survey items do not already exist in the published
literature, the researchers must create their own items, based on their review of the existing literature and
their own expertise. Often, a focus group of experts can also help to create items. For example, if a


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company wants to assess its employees' attitudes towards an intended change in work rules, the researcher
may lead a focus group of several experienced company managers to capture all of the relevant ideas that
need to be addressed by the survey. Before the survey instrument is sent out, it must be tested for
reliability and validity. Reliability refers to how consistently the instrument measures, and validity refers
to whether the instrument is measuring.

One concern when designing a survey is how to word the items. One of the most popular ways to measure
attitudes on a survey is by using the Likert scale. This method presents a series of statements to
respondents for which they are asked to indicate the degree to which they agree with the statements. An
example of a statement might be "The sales people are helpful." Respondents are asked to indicate the
degree to which they agree with the statements by checking either SA (strongly agree), A (agree), N
(neither agree nor disagree), D (disagree), or SD (strongly disagree). Respondents' answers would then be
scored where SA = 5, A = 4, N = 3, D = 2, and SD = 1. A total score would be computed by average or
summing scores on related items.

SAMPLING.

When administering a questionnaire there are two options as to who should complete the survey. Option
one is to give the questionnaire to everyone in the targeted population. This is called a census. However, a
census is usually not practical or cost effective. For instance, you may not be able to survey every one of
your customers from last year to determine levels of customer satisfaction with your products.
Consequently, in order to save time and money, only a sample or subset of the target population receives
the questionnaire.

When selecting individuals for a sample, either a probability approach or a nonprobability approach can
be used. Probability samples are those where each element of the population has a known probability of
being selected. A random sample, for example, is the case where each element has the same probability of
being selected. There are some specific types of nonprobability samples: convenience samples, judgment
samples, and quota samples. Convenience samples are chosen at the convenience of the researcher. For
example, a researcher might distribute a survey to all customers who enter one retail store in a one-week
period to determine their level of customer satisfaction with the company's products. This sample is rather
easy to select, but it may not represent the full range of customers who have used that product. In a
judgment sample, individuals are selected by the researcher because they are believed to represent the
population under study. Quota samples attempt to make the sample representative of the population under
study where quotas are set for specific groups of people, which are generally selected on the basis of
demographic characteristics.

The chief advantage of a probability sample over a nonprobability sample is the ability to assess the
reliability and the amount of sampling error in the results. For example, if the goal were to estimate the


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annual household income for a given county, probability sampling would allow an accuracy assessment
of the estimate. This could not be accomplished with a nonprobability sample.

SURVEY ADMINISTRATION.

After the survey has been designed and its reliability and validity assessed, the company must decide the
administration method that it will use. Each administration method has its own advantages and
disadvantages in terms of cost, information control, sampling control, and administrative control.
Information control refers to the possible variation in responses to questions. Sampling control is the
ability to select cooperative respondents. Administrative control refers to factors affecting the efficiency
of the survey, including timing, quality control, and standardization.

Personal interviews are generally the most expensive means of data collection. In a company, this would
mean having researchers meet with employees one-on-one to ask them the survey questions and record
their responses. One of the main advantages of the personal interview is the ability to ask any type of
question, including an open-ended question, and to adapt to the respondent's answers. However, in
addition to being expensive and time consuming, this method is not anonymous, and therefore
respondents may be reluctant to answer questions that they feel are sensitive or invasive.

The mail questionnaire is usually the least expensive method of data collection. Besides cost savings,
another advantage of the mail questionnaire is its wide distribution potential. However, mail
questionnaires cannot control the speed of responses, and the researcher cannot explain ambiguous
questions. Mail questionnaires are probably best utilized when asking personal or sensitive questions,
particularly if the survey can be made anonymous. Questionnaires can be circulated using various
methods, such as post, electronic mail, and fax.

The telephone interview is associated with relatively low cost and higher response rates, and is one of the
fastest methods of data collection. While there are methods to address the problem, unlisted numbers
make it more difficult to obtain representative samples. Establishing rapport is also more difficult in
telephone interviewing than in the personal interview.

One survey administration method that is growing in popularity is the Internet survey, in which
respondents answer items on a survey that is located on a web site. Newer, specialized software products
are making it easier to conduct online surveys, even for those people with little to no computer
programming skills. Studies indicate that Internet research can result in faster responses, lower costs,
higher response rates, and better flexibility. Additionally, this method aids in data administration, since
survey responses can be directly inserted into a data spreadsheet by the web survey software.




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INCREASING RESPONSE RATES.

One of the main concerns of survey research is the response rate, or the number of people who are asked
to complete a survey who actually do. Nonresponse error is a source of bias because of the failure to get
answers from some of the sample. "Not-at-homes" plague the telephone survey and uncooperative
respondents affect telephone, mail, Internet, and personal interview surveys. While research results are
mixed regarding effective means for increasing response rates, the following represent some ideas for
increasing response rates:

          give respondents advance notice of the survey
          guarantee confidentiality or anonymity
          provide monetary incentives
          provide a postage-paid return envelope for mail surveys
          personalize outgoing envelopes

DATA ANALYSIS

Research provides data, and it is the task of the researcher to transform the collected data into useful
information for management. The first step in data analysis is preparing the data by editing it for several
factors, including:

          completeness—checking for any omissions
          legibility—making sure that handwriting is understandable so that answers will be coded
           correctly
          comprehensibility—making sure the answer is understandable
          consistency—checking for consistent answers from the respondent
          uniformity—checking to see that responses are recorded in the same manner

Once the data is edited it is ready for coding, which is determining how survey responses will be
transformed into numerical data. The first step in coding is the development of a codebook. The codebook
formalizes the coding process by listing answers and their accompanying codes. After the data is coded
and entered into a data spreadsheet, statistical analyses can be performed to create useful information for
the researchers. If there are hypotheses to be tested, the researcher is in a position to use the gathered data
to test the hypotheses. Data analysis could be as simple as reporting descriptive statistics such as
averages, measures of variability, and percentages, or if needed, advance statistical techniques could be
applied.




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RESEARCH REPORT

The research report can be as simple as a short report of a few pages giving the overall findings of the
research, or it can be a long report with numerous parts. The degree of formality required by management
dictates the type of report to prepare. Figure 2 presents the order of inclusion of the various parts of a long
formal report.




Figure 2
Parts of a Complete Research Report

PREFATORY SECTION.

In this part of the report, first a title fly needs to be prepared. The title fly only includes the title of the
report. The title should be carefully worded so it tells the reader exactly what the report is about.
Following the title fly is the title page. The title page should include the title of the report, the name and
the title of the recipient of the report, and the name and the title of the individual who prepared the report
and the date. The letter that authorized the undertaking of the research project, followed by a letter of
transmittal indicating the completion of the research report are the next items included in the report.
Include a table of contents followed by an executive summary. The executive summary, summarizing the
report's major findings, should be brief and to the point. This summary should briefly explain the
conclusions.




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INTRODUCTION TO THE RESEARCH.

This section of the report provides a clear background and statement of the research question and provides
information about the objectives of the research. Included in this section would be a literature review
about previous studies with the same or similar problem. If there are hypotheses to be tested, population
parameters to be estimated, theories to be considered, they will be incorporated into this section of the
report

RESEARCH METHOD.

This section will provide a detailed explanation of research design and will provide answers to many
questions. What type of design was used? What instruments were used for the collection of data? Were
there any subjects involved in the study? What did the subjects do? How was the sample selected? What
kind of statistical or non-statistical techniques were used for data analysis? Finally, in this section of the
report the limitations encountered in the study should be presented.

FINDINGS.

This section is probably one of the most important parts of the research report. Provided in this section
would be the results of the data analyses and explanation of all the findings. At this point, all the raw data
have been analyzed and converted to meaningful information for management's use. This is the section
where the original research question is answered.

SUMMARY, CONCLUSIONS, AND RECOMMENDATIONS.

A concise yet precise summary of major findings will be included in this section, followed by any
recommendations that the researcher considers important and meaningful.

APPENDICES AND BIBLIOGRAPHY.

Statistical tests, large tables of information, copies of measurement instruments, and supporting
documents should be included in the appendices. Finally, the report should end by providing a
bibliography of all sources of information.


****** Please don’t copy this exactly. Read carefully, make inferences and then write the solution with
referring an example from any organization (whether big or small) you know. Regards, Pinkki
Manohar




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2.      What is a Thurstone’s Equal-Appearing Interval Scale? What are its objectives? Discuss the
        advantages and limitations of Thurstone’s Equal-Appearing Interval Scale.

Solution :

hurstone Scaling


Thurstone was one of the first and most productive scaling theorists. He actually invented three different
methods for developing a unidimensional scale: the method of equal-appearing intervals; the method
of successive intervals; and, the method of paired comparisons. The three methods differed in how the
scale values for items were constructed, but in all three cases, the resulting scale was rated the same way
by respondents. To illustrate Thurstone's approach, I'll show you the easiest method of the three to
implement, the method of equal-appearing intervals.

The Method of Equal-Appearing Intervals

Developing the Focus. The Method of Equal-Appearing Intervals starts like almost every other scaling
method -- with a large set of statements. Oops! I did it again! You can't start with the set of statements --
you have to first define the focus for the scale you're trying to develop. Let this be a warning to all of you:
methodologists like me often start our descriptions with the first objective methodological step (in this
case, developing a set of statements) and forget to mention critical foundational issues like the
development of the focus for a project. So, let's try this again...


The Method of Equal-Appearing Intervals starts like almost every other scaling method -- with the
development of the focus for the scaling project. Because this is a unidimensional scaling method, we
assume that the concept you are trying to scale is reasonably thought of as one-dimensional. The
description of this concept should be as clear as possible so that the person(s) who are going to create the
statements have a clear idea of what you are trying to measure. I like to state the focus for a scaling
project in the form of a command -- the command you will give to the people who will create the
statements. For instance, you might start with the focus command:


Generate statements that describe specific attitudes that people might have towards persons with
AIDS.

You want to be sure that everyone who is generating statements has some idea of what you are after in
this focus command. You especially want to be sure that technical language and acronyms are spelled out
and understood (e.g., what is AIDS?).

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Generating Potential
Scale Items. Now, you're
ready to create
statements. You want a
large set of candidate
statements (e.g., 80 --
100) because you are
going to select your final
scale items from this
pool. You also want to be
sure that all of the statements are worded similarly -- that they don't differ in grammar or structure. For
instance, you might want them each to be worded as a statement which you cold agree or disagree with.
You don't want some of them to be statements while others are questions.


For our example focus on developing an AIDS attitude scale, we might generate statements like the
following (these statements came from a class exercise I did in my Spring 1997 undergrad class):


       people get AIDS by engaging in immoral behavior
       you can get AIDS from toilet seats
       AIDS is the wrath of God
       anybody with AIDS is either gay or a junkie
       AIDS is an epidemic that affects us all
       people with AIDS are bad
       people with AIDS are real people
       AIDS is a cure, not a disease
       you can get AIDS from heterosexual sex
       people with AIDS are like my parents
       you can get AIDS from public toilets
       women don’t get AIDS
       I treat everyone the same, regardless of whether or not they have AIDS
       AIDS costs the public too much
       AIDS is something the other guy gets


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      living with AIDS is impossible
      children cannot catch AIDS
      AIDS is a death sentence
      because AIDS is preventable, we should focus our resources on prevention instead of curing
      People who contract AIDS deserve it
      AIDS doesn't have a preference, anyone can get it.
      AIDS is the worst thing that could happen to you.
      AIDS is good because it will help control the population.
      If you have AIDS, you can still live a normal life.
      People with AIDS do not need or deserve our help
      By the time I would get sick from AIDS, there will be a cure
      AIDS will never happen to me
      you can't get AIDS from oral sex
      AIDS is spread the same way colds are
      AIDS does not discriminate
      You can get AIDS from kissing
      AIDS is spread through the air
      Condoms will always prevent the spread of AIDS
      People with AIDS deserve what they got
      If you get AIDS you will die within a year
      Bad people get AIDS and since I am a good person I will never get AIDS
      I don't care if I get AIDS because researchers will soon find a cure for it.
      AIDS distracts from other diseases that deserve our attention more
      bringing AIDS into my family would be the worst thing I could do
      very few people have AIDS, so it's unlikely that I'll ever come into contact with a sufferer
      if my brother caught AIDS I'd never talk to him again
      People with AIDS deserve our understanding, but not necessarily special treatment
      AIDS is a omnipresent, ruthless killer that lurks around dark alleys, silently waiting for naive
       victims to wander passed so that it might pounce.
      I can't get AIDS if I'm in a monogamous relationship
      the nation's blood supply is safe
      universal precautions are infallible
      people with AIDS should be quarantined to protect the rest of society


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      because I don't live in a big city, the threat of AIDS is very small
      I know enough about the spread of the disease that I would have no problem working in a health
       care setting with patients with AIDS
      the AIDS virus will not ever affect me
      Everyone affected with AIDS deserves it due to their lifestyle
      Someone with AIDS could be just like me
      People infected with AIDS did not have safe sex
      Aids affects us all.
      People with AIDS should be treated just like everybody else.
      AIDS is a disease that anyone can get if there are not careful.
      It's easy to get AIDS.
      The likelihood of contracting AIDS is very low.
      The AIDS quilt is an emotional reminder to remember those who did not deserve to die painfully
       or in vain
      The number of individuals with AIDS in Hollywood is higher than the general public thinks
      It is not the AIDS virus that kills people, it is complications from other illnesses (because the
       immune system isn't functioning) that cause death
      AIDS is becoming more a problem for heterosexual women and their offsprings than IV drug
       users or homosexuals
      A cure for AIDS is on the horizon
      A cure for AIDS is on the horizon
      Mandatory HIV testing should be established for all pregnant women




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Rating the Scale Items. OK, so now you have a set of statements. The next step is to have your
participants (i.e., judges) rate each statement on a 1-to-11 scale in terms of how much each statement
indicates afavorable attitude towards people with AIDS. Pay close attention here! You DON'T want the
participants to tell you what their attitudes towards AIDS are, or whether they would agree with the
statements. You want them to rate the "favorableness" of each statement in terms of an attitude towards
AIDS, where 1 = "extremely unfavorable attitude towards people with AIDS" and 11 = "extremely
favorable attitude towards people with AIDS.". (Note that I could just as easily had the judges rate how
much each statement represents a negative attitude towards AIDS. If I did, the scale I developed would
have higher scale values for people with more negative attitudes).




Computing Scale Score Values for Each Item. The next step is to analyze the rating data. For each
statement, you need to compute the Median and the Interquartile Range. The median is the value above

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and below which 50% of the ratings fall. The first quartile (Q1) is the value below which 25% of the
cases fall and above which 75% of the cases fall -- in other words, the 25th percentile. The median is the
50th percentile. The third quartile, Q3, is the 75th percentile. The Interquartile Range is the difference
between third and first quartile, or Q3 - Q1. The figure above shows a histogram for a single item and
indicates the median and Interquartile Range. You can compute these values easily with any introductory
statistics program or with most spreadsheet programs. To facilitate the final selection of items for your
scale, you might want to sort the table of medians and Interquartile Range in ascending order by Median
and, within that, in descending order by Interquartile Range.

*****refer http://www.socialresearchmethods.net/kb/scalthur.php Regards, Pinkki Manohar****




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Q. 3. In order to increase their efficiency, one group of operators was imparted classroom training, and
         the other group was provided on the job training. After the training, the times to complete a
         certain job in minutes, was recorded for both the groups, the data recorded is given in the
         following table.

                                 Classroom Training     On Job Training
                                 Operator No- Time      Operator No- Time
                                 1             35       1              85
                                 2             39       2              28
                                 3             51       3              42
                                 4             63       4              37
                                 5             48       5              61
                                 6             31       6              54
                                 7             29       7              36
                                 8             41       8              57
                                 9             55


Solution : not available******

4.        Write short note on the following:

         a)   Decision-making Unit
         b)   Type I & II Error
         c)   Latin Square design
         d)   Copy reading of the reports preparation

Solution :

         a) The Decision-making Unit
         The Decision-making Unit consists of members from different parts of the organisation,each of
          them having some interest in the result of the purchasing efforts (Varey, 2002), andplaying any of
          five roles in the buying decision process (Kotler et al., 2002):
         Users are members of the organisation who will use the product or service. In manycases, users
          initiate the buying proposal and help define product specifica- tions.
         Influencers are people who influence the buying decision. They often help define specifi-cations
          and also provide information for evaluating alternatives. Technicalpersonnel are particularly
          important influencers.
         Buyers are people with formal authority to select the supplier and organize terms ofpurchase.
          Buyers may help outline product specifications, but they play theirmost important role in
          selecting vendors and in negotiating. In more complexpurchases, buyers might include high-level
          officers participating in the nego-tiations.
         Deciders are people who have formal or informal control to select or approve the finalsuppliers.
          In routine buying, the buyers are often the deciders or at least theapprovers of the purchase.
         Gatekeepersare people who control the flow of information to others. For instance, gate-

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       keepers could be agents who often have the authority to prevent salespeoplefrom meeting users or
        deciders. Other examples of gatekeepers include tech-nical personnel and even personal
        secretaries.
       The number of individuals involved in purchasing will depend on the complexity of theneed, the
        value of the purchase and the level of risk held to be connected to the decision.The people taking
        on the different roles of the DMU vary with each purchasing occasion,but it is important for
        suppliers to identify the members of the DMU and recognize theirparticular needs so that
        communication efforts can be customized in each single case. Therequirements for particular
        marketing communication efforts are dependant on the charac-ters of the buying circumstances
        and the influences on industrial buying behaviour stemfrom the buying organisation itself, from
        stakeholders, and from the interpersonal relation-ships of the DMU members (Varey, 2002).
       According to Morris et al.(2001), the mechanism of the DMU is of critical importance tothe B2B
        marketer. Morris (1992) states that one approach to clarify what takes place amongthe
        participants in the purchasing decision process is to focus on the structure of theDMU. Since the
        DMU is normally not a formal group, its structure is not formally estab-lished by the
        organisation. Instead, the structure of the DMU is determined by communica-tion linkages among
        the members. Depending on the nature of the purchase, differentpeople from different levels in
        the organisation will be involved in the purchase decision.Hence, to be able to reach the most
        important individuals in each purchasing situation, theseller must clarify the structure of the
        DMU.


******refer http://www.scribd.com/doc/12241603/16/The-Decision-making-Unit

        b) Type I & II Error

Type I and Type II

Statisticians note two sorts of statistical error. There is a "null hypothesis" that corresponds to a presumed
default "state of nature", e.g., an individual is free of disease, an accused is innocent. The "alternative
hypothesis" corresponds to the opposite situation, that is, the individual has the disease, the accused is
guilty. The goal is to determine accurately if the null hypothesis can be discarded in favor of the
alternative. A test of some sort is conducted and data are obtained. The result of the test may be negative
(that is, it does not indicate disease, guilt). On the other hand, it may be positive (that is, it may indicate
disease, guilt). If the result of the test does not correspond with the actual state of nature, then an error has
occurred, but if the result of the test corresponds with the actual state of nature, then a correct decision has
been made. There are two kinds of error, classified as "type I error" and "type II error," depending upon
which hypothesis has incorrectly been identified as the true state of nature
Type I error

Type I error, also known as an "error of the first kind", an α error, or a "false positive": the error of
rejecting a null hypothesis when it is actually true. Plainly speaking, it occurs when we are observing a
difference when in truth there is none, thus indicating a test of poor specificity. An example of this would




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be if a test shows that a woman is pregnant when in reality she is not, or telling a patient he is sick when
in fact he is not. Type I error can be viewed as the error of excessive credulity

or even hallucination. In terms of folk tales, an investigator may be "crying wolf" (setting a false alarm)
without knowing it.

In other words, a Type I error means that a positive inference is actually false.
Type II error

Type II error, also known as an "error of the second kind", a β error, or a "false negative": the error of
failing to reject a null hypothesis when in fact we should have rejected it. In other words, this is the error
of failing to observe a difference when in truth there is one, thus indicating a test of poor sensitivity. An
example of this would be if a test shows that a woman is not pregnant, when in reality, she is. Type II
error can be viewed as the error of excessive skepticism

or myopia. The investigator does not see the wolf at the door.

In other words, a Type II error means that a negative inference is actually false.

See Various proposals for further extension, below, for additional terminology.

A table as follows can be useful in understanding the concepts.


Null Hypothesis (H0) is true Alternative Hypothesis (H1) is true


                                                                          Wrong decision
Fail to Reject Null Hypothesis               Right decision                Type II Error
                                                                          False Negative


                                            Wrong decision
Reject Null Hypothesis                       Type I Error                  Right decision
                                            False Positive



Understanding Type I and Type II errors

When an observer makes a Type I error in evaluating a sample against its parent population, he or she is
mistakenly thinking that a statistical difference exists when in truth there is no statistical difference (or, to
put another way, the null hypothesis should not be rejected but was mistakenly rejected). For example,
imagine that a pregnancy test has produced a "positive" result (indicating that the woman taking the test is
pregnant); if the woman is actually not pregnant though, then we say the test produced a "false positive"


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(assuming the null hypothesis, Ho, was that she is not pregnant). A Type II error, or a "false negative", is
the error of failing to reject a null hypothesis when the alternative hypothesis is the true state of nature.
For example, a type II error occurs if a pregnancy test reports "negative" when the woman is, in fact,
pregnant.

From the Bayesian point of view, a type one error is one that looks at information that should not
substantially change one's prior estimate of probability, but does. A type two error is that one looks at
information which should change one's estimate, but does not. (Though the null hypothesis is not quite
the same thing as one's prior estimate, it is, rather, one's pro forma prior estimate.)

In summary:

   Rejecting a null-hypothesis when it should not have been rejected creates a type I error.
   failing to reject a null-hypothesis when it should have been rejected creates a type II error.
   (In either case, a wrong decision or error in judgment has occurred.)
   Decision rules (or tests of hypotheses), in order to be good, must be designed to minimize errors of
    decision.
   Minimizing errors of decision is not a simple issue—for any given sample size the effort to reduce
    one type of error generally results in increasing the other type of error.
   Based on the real-life application of the error, one type may be more serious than the other.
   (In such cases, a compromise should be reached in favor of limiting the more serious type of error.)
   The only way to minimize both types of error is to increase the sample size, and this may or may not
    be feasible.

   Hypothesis testing is the art of testing whether a variation between two sample distributions can be
    explained by chance or not. In many practical applications type I errors are more delicate than type II
    errors. In these cases, care is usually focused on minimizing the occurrence of this statistical error.
    Suppose, the probability for a type I error is 1% , then there is a 1% chance that the observed
    variation is not true. This is called the level of significance. While 1% might be an acceptable level of
    significance for one application, a different application can require a very different level. For
    example, the standard goal of six sigma is to achieve precision to 4.5 standard deviations above or
    below the mean. This means that only 3.4 parts per million are allowed to be deficient in a normally
    distributed process. The probability of type I error is generally denoted with the Greek letter alpha, α.

   To state it simply, a type I error can usually be interpreted as a false alarm or under-active specificity.
    A type II error could be similarly interpreted as an oversight, but is more akin to a lapse in attention
    or under-active sensitivity. The probability of type II error is generally denoted with the Greek letter
    beta, β.


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           c) Latin Square design
           d) n combinatorics and in experimental design, a Latin square is an n × n array filled
               with n different Latin letters, each occurring exactly once in each row and exactly once in each
               column. Here is an example:


                                               A        B        C


                                               C        A        B


                                               B        C        A


           e) The name "Latin square" is motivated by mathematical papers by Leonhard Euler, who
               used Latincharacters as symbols. Of course, other symbols can be used instead of Latin letters:
               in the above example, the alphabetic sequence A, B, C can be replaced by the integer sequence
               1, 2, 3.


Overview of uses

Latin squares are used in statistics and in mathematics.

       In the design of experiments, Latin squares are a special case of row-column designs for
    two blocking factors:
Many row-column designs are constructed by concatenating Latin squares. In algebra, Latin
squares are generalizations of groups; in fact, Latin squares are characterized as being
the multiplication tables (Cayley tables) of quasigroups. Other applications include error correcting
codes. Reduced form

A Latin square is said to be reduced (also, normalized or in standard form) if both its first row and its first
column are in their natural order. For example, the above Latin square is not reduced because its first
column is A, C, B rather than A, B, C.

We can make any Latin square reduced by permuting (reordering) the rows and columns. Here switching
the above matrix's second and third rows yields


    A     B     C


    B     C     A



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 C     A     B


which is reduced: Both its first row and its first column are alphabetically ordered A, B, C.
Properties

[edit]Orthogonal array representation

If each entry of an n × n Latin square is written as a triple (r,c,s), where r is the row, c is the column,
and s is the symbol, we obtain a set ofn2 triples called the orthogonal array representation of the square.
For example, the orthogonal array representation of the first Latin square displayed above is:

        { (1,1,1),(1,2,2),(1,3,3),(2,1,2),(2,2,3),(2,3,1),(3,1,3),(3,2,1),(3,3,2) },

     where for example the triple (2,3,1) means that in row 2 and column 3 there is the symbol 1. The
     definition of a Latin square can be written in terms of orthogonal arrays:

      A Latin square is the set of all triples (r,c,s), where 1 ≤ r, c, s ≤ n, such that all ordered pairs (r,c)
           are distinct, all ordered pairs (r,s) are distinct, and all ordered pairs (c,s) are distinct.

     For any Latin square, there are n2 triples since choosing any two uniquely determines the third.
     (Otherwise, an ordered pair would appear more than once in the Latin square.)

     The orthogonal array representation shows that rows, columns and symbols play rather similar roles,
     as will be made clear below.
Equivalence classes of Latin squares

Many operations on a Latin square produce another Latin square (for example, turning it upside down).

If we permute the rows, permute the columns, and permute the names of the symbols of a Latin square,
we obtain a new Latin square said to be isotopic to the first. Isotopism is an equivalence relation, so the
set of all Latin squares is divided into subsets, called isotopy classes, such that two squares in the same
class are isotopic and two squares in different classes are not isotopic.

Another type of operation is easiest to explain using the orthogonal array representation of the Latin
square. If we systematically and consistently reorder the three items in each triple, another orthogonal
array (and, thus, another Latin square) is obtained. For example, we can replace each triple (r,c,s) by
(c,r,s) which corresponds to transposing the square (reflecting about its main diagonal), or we could
replace each triple (r,c,s) by (c,s,r), which is a more complicated operation. Altogether there are 6
possibilities including "do nothing", giving us 6 Latin squares called the conjugates (also parastrophes) of
the original square.




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Finally, we can combine these two equivalence operations: two Latin squares are said to be paratopic,
also main class isotopic, if one of them is isotopic to a conjugate of the other. This is again an equivalence
relation, with the equivalence classes called main classes, species, or paratopy classes. Each main class
contains up to 6 isotopy classes.
Number

There is no known easily-computable formula for the number L(n) of n × n Latin squares with symbols
1,2,...,n. The most accurate upper and lower bounds known for large n are far apart. One classic result is




      (this given by van Lint and Wilson).

      Here we will give all the known exact values. It can be seen that the numbers grow exceedingly
      quickly. For each n, the number of Latin squares altogether (sequence A002860 in OEIS) is n! (n-1)!
      times the number of reduced Latin squares (sequence A000315 in OEIS).

                             The numbers of Latin squares of various sizes

  n            reduced Latin squares of size n                                  all Latin squares of size n


  1                                           1                                                          1


  2                                           1                                                          2


  3                                           1                                                         12


  4                                           4                                                        576


  5                                          56                                                    161280


  6                                       9408                                                 812851200


  7                                  16942080                                           61479419904000


  8                             535281401856                                   108776032459082956800


  9                     377597570964258816                            5524751496156892842531225600



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  1
               7580721483160132811489280                9982437658213039871725064756920320000
  0


  1     5363937773277371298119673540771 77696683617177014410744434673423068231106560
  1                                 840                                         0000


      For each n, each isotopy class (sequence A040082 in OEIS) contains up to (n!)3 Latin squares (the
      exact number varies), while each main class (sequence A003090 in OEIS) contains either 1, 2, 3 or
      6 isotopy classes.

                                 Equivalence classes of Latin squares

                  n                      main classes                   isotopy classes


                  1                                 1                                 1


                  2                                 1                                 1


                  3                                 1                                 1


                  4                                 2                                 2


                  5                                 2                                 2


                  6                                12                                22


                  7                              147                               564


                  8                           283657                           1676267


                  9                     19270853541                     115618721533


                  10            34817397894749939                208904371354363006


                  11 2036029552582883134196099 12216177315369229261482540

Examples

We give one example of a Latin square from each main class up to order 5.


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They present, respectively, the multiplication tables of the following groups:

   {0} – the trivial 1-element group
       – the binary group
       – cyclic group of order 3
                – the Klein four-group
       – cyclic group of order 4
       – cyclic group of order 5
   the last one is an example of a quasigroup, or rather a loop, which is not associative.



Applications

Error correcting codes

Sets of Latin squares that are orthogonal to each other have found an application as error correcting
codes in situations where communication is disturbed by more types of noise than simple white noise,
such as when attempting to transmit broadband Internet over powerlines

Firstly, the message is sent by using several frequencies, or channels, a common method that makes the
signal less vulnerable to noise at any one specific frequency. A letter in the message to be sent is encoded
by sending a series of signals at different frequencies at successive time intervals. In the example below,
the letters A to L are encoded by sending signals at four different frequencies, in four time slots. The
letter C for instance, is encoded by first sending at frequency 3, then 4, 1 and 2.


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The encoding of the twelve letters are formed from three Latin squares that are orthogonal to each other.
Now imagine that there's added noise in channels 1 and 2 during the whole transmission. The letter A
would then be picked up as:



In other words, in the first slot we receive signals from both frequency 1 and frequency 2; while the third
slot has signals from frequencies 1, 2 and 3. Because of the noise, we can no longer tell if the first two
slots were 1,1 or 1,2 or 2,1 or 2,2. But the 1,2 case is the only one that yields a sequence matching a letter
in the above table, the letter A. Similarly, we may imagine a burst of static over all frequencies in the
third slot:



Again, we are able to infer from the table of encodings that it must have been the letter A being
transmitted. The number of errors this code can spot is one less than the number of time slots. It has also
been proved that if the number of frequencies is a prime or a power of a prime, the orthogonal Latin
squares produce error detecting codes that are as efficient as possible.



d) Copy reading of the reports preparation
   The copy reader takes the story as it comes from the reporter and puts it through a refining process.
   His work is critical rather than creative. It is destructive so far as errors of grammar, violations of
   news style and libel are concerned. But if his sense of news is keen, as that of every copy reader
   should be, he will find abundant opportunity for something more than mechanical deletion and
   interlineation. He may insert a terse bit of ex-planation to clear away obscurity. or may add a piquant
   touch that will redeem a story from dullness. To the degree that he edits news with sympathy and
   understanding, with a clear perception of news values, his work may be regarded as creative. If, on
   the other hand, he conceives it his duty to reduce all writing to a dead level of mediocrity, if his ideal
   of editing is merely to wage war on the split infinitive and substitute "obtain" for "secure," no matter
   what the sense, he richly deserves the epithet that is certain to be hurled at the copy reader by the
   reporter whose fine phrases have been cut out — he is in truth a " butcher " of copy.

    QUALIFICATIONS FOR THE WORK
    The efficient copy reader has a good working knowledge of the English language; he has a highly
    developed sense of news; he knows the style of his paper; he is content with nothing short of
    accuracy. To write headlines, he must have primarily the knack of putting the gist of a story into a
    few short, simple words. With all these qualifications he may yet fail if he is not able, when occasion

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   demands, to work swiftly. It follows that he should keep in touch with current affairs and should lose
   no opportunity to add to his stock of knowledge of the city in which he works. The name of the
   Secretary of the Interior, the latest development in a famous will case, whether a thoroughfare is a
   street or an avenue, the initials of the county recorder — all such details can be found in the files of
   the newspaper or in reference books, but the copy reader can save valuable time if he has them filed
   away in his memory. New words are constantly coming into general use and new ideas are
   demanding expression. The copy reader must keep abreast of the big movements in science, in
   politics, in all the fields from which news stories are drawn. The right attitude toward his work was
   shown by a copy reader who, when ballooning first gave evidence of becoming a popular sport, went
   to the public library and looked in the index for " aeronautics." He got the best book he could find on
   the subject and studied it. He learned the principles of ballooning and its special vocabulary and when
   stories of the new sport began to come to him, he was able to " blue-pencil " the copy intelligently.

   ORGANIZATION OF COPY READERS
   The number of copy readers depends, of course, upon the size of the newspaper. Small-city papers
   may have no men employed solely for this work. On the larger papers the staff of copy readers aver-
   ages perhaps six or seven, while some offices use as many as a dozen or more. These men are said to
   comprise the " copy desk," and all news copy, in theory at least, passes through their hands. On some
   papers the staff is divided, part reading telegraph copy under the telegraph editor and part working in
   the local room under the city editor. Other offices have adopted the newer plan of the combined desk,
   where both telegraph and local copy is read. This desk is in charge of a head copy reader, who
   apportions the copy among the readers, passes on their work after it is finished, and in general keeps
   things moving. The head copy reader is in effect a news editor or an assistant news editor. It is his
   duty to see that neither the local nor the telegraph department plays up " its stories unduly, but that
   each story, whatever its source, is rated at its true value in relation to the other news of the day.

   EDITING THE STORY
   The work of the copy reader is twofold : (1) to edit the copy and (2) to write the head.
   In brief, the copy reader should hew and polish the story to exactly the form in which it should appear
   in print. He is a skilled workman, employed to trim away the rough edges. By this it is not meant that
   the copy reader is expected to give the story the grace and elegance of literature. He should give it, if
   it has not already, grammatical exactness, freedom from ambiguity, and the force that goes with
   direct, simple statement of fact. This is the groundwork of the copy reader's task — to make the story
   correct in form as in fact.
   Less obviously, he must make the story conform to style— not only to the general laws of news
   writing, but to the special, arbitrary style of the newspaper for which it is written. Every good
   newspaper has an individuality, expressed partly in what is rather vaguely termed its style. The
   general style of a newspaper, its habitual attitude toward news, can be learned only by close
   observation of its columns. Specific rules, however, are laid down to cover the more mechanical
   aspects of style, such as punctuation and capitalization. No two newspapers agree in all the details of
   style.




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