# EG381 Statistics �Introduction to Statistics� by 2nHCYXa

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```									     EG381 Statistics

“Introduction to Statistics”

E381 – Statistics
Mr. Thomas Rich
Week 1
Objectives for this Lecture
1. Review class syllabus and class
structure
2. Define the fundamental terms used in
statistics
3. Classify qualitative and quantitative
data with regard to four levels of
measurement
4. Explain the different types of data
collected
5. Identify sampling techniques for a
given sample
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Let’s start by introducing ourselves

CLASS INTRODUCTIONS

3
Next let’s examine the Class Syllabus...

Questions?

Acknowledgement Forms

Reiterate Some Important Points

4
We are truly in an “information age”....data is
abundant, and usually free and easily accessible...
Examples:
Impact of violent TV program on Children

Outsourcing and its effects on the
economy

Global Warming

Today the issue is usually not “we need
more data”....but “how do we use our data
to make decisions”
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Data is Abundant in Today’s Organizations…

Most companies have information
systems that yield tremendous amounts of
data:

Systems usage and frequency
Web Page “Hits”
Revenue and Sales
Quality Control
Individual Performance Metrics

What Data is Collected at Your Job?
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Class Discussion Question....

What are some of your goals or
hopes in taking this course, and
what do you believe will be the
benefits of taking a Statistics
class?

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What is “Statistics”??

Let’s hear from several of you on what you
think the study of “statistics” is defined as...

“Statistics is defined as the science of
collecting, organizing, analyzing, and
interpreting data in order to make decisions.
It uses mathematical formulas for analysis,
and it involves the understanding and
interpretation of the results.”

Look at examples on page 2....
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So to understand “Statistics” we have to
understand the meaning of the word “data”...
When we use the word “data” we mean:

RAW DATA

We get data from
observations
counts
measurements

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Two different types of data sets...

“Population” – all the data that is of
interest
“Sample” – a subset of the population
GPA’s of All ITT Tech Jax Students

GPA of ITT Tech Jax Students
in EG381

For what reasons do we collect “samples” from
populations? Why don’t we gather the entire
population?                      10
Determine if the data set is
“population” or “sample”
- The age of each state governor
- A satisfaction survey taken of all
ITT Tech students
- The salary of 5 randomly chosen
baseball players
- The weights of every fifth baby born
in March at St. Luke’s

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Two Major Branches of Statistics

I. Descriptive Statistics

II. Inferential Statistics

Look in your text at these definitions – p. 5

Which is the branch that involves organization,
summarization, and display of data?

Which is the branch that involves use of a sample
to draw conclusions about a population?

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Decide which part of the study represents the
descriptive branch. What inferences might be
drawn?
- “A survey of home mortgages in Jacksonville
shows that foreclosures are increased 23%
over last year.”

-   “A large sample of college students was
studied over 10 years after their graduation,
and their salaries increased on average 22%
more than a comparative sample who did not

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Two ways to classify data....

I. Qualitative – attributes, labels,
non-numeric
II. Quantitative – measurements or
counts

Examples – classify the following
Hair Color
Phone Numbers
RAM size in a computer
Brand Name
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We also classify data according to the
“level of measurement”
Nominal – qualitative only

Ordinal – qualitative or quantitative

Interval - quantitative

Ratio – quantitative
Look at Chart on Page 12
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Experimental Design....basic steps to
designing a statistical study
1. Identify the variables of interest and the
population
2. Develop plan for data collection
3. Collect the data
4. Describe the data using descriptive
statistics
5. Interpret the data and make inferences and
conclusions
6. Identify sources of error
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When we collect data, we can do a
“census” or we can “sample”
data

Sample: “carefully selected
subset” of the data

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Different methods of collecting samples
Simple Random Sample
Random Samples: every member
of the population has an equal
chance of being selected.
Examples?

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Different methods of collecting samples
Stratified Sample
Stratified: sampling a little from
defined classifications (or “strata”)
of data
Examples?

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Different methods of collecting samples
Cluster Sample
Cluster Sampling: sometimes data
is broken into subgroups, each
having similar characteristics
Examples?

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Different methods of collecting samples
Systematic Sampling
Systematic – sampling every nth
event
Examples?

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Different methods of collecting samples
Convenience Sampling
Convenience – selecting data,
well, as you can…
Examples?

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In Class Activities

In your groups you will work on
the in-class activities. When
your group is done, come to the
instructor to review your

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Homework #1
Due Next Week:
Section 1.1: #24, #30
Section 1.2: #12, #14
Section 1.3: #8, #15
Must be typed, Arial Font, 12 point type,
double spaced
Due: Beginning Class