# Sp Stats Review Worksheet 3 Answers - PowerPoint

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```					Correlational Research

301 Lab
Week 2 - Thursday
Agenda for Today:
 1. Turn in observational Method & Results
 2. Discuss correlation & survey methods
 3. Discuss research reading tips
 4. Class survey & data entry using SPSS
Announcements:
 Regarding last week’s homework (observation
summary, data, & worksheet): I will hold on to that to
aid me in grading the Methods & Results that you
did for today.
 Quiz #2 is on Tuesday (6/20). You may have your
article out during the quiz, as well as any
notes/books, but be sure to read the article
beforehand.
What are correlations?

   We use correlational research when we
cannot assign experimental groups due to
ethics or practicality. For example, smoking
or gender.
   In correlational research we look to see if one
variable changes with another (covaries).
   We can also call this an association.
Correlations

   Assess the relationships among naturally
occurring variables with the goal of identifying
predictive relationships.
   *Degree & Direction*
THE MOST IMPORTANT RULE IN
CORRELATIONAL RESEARCH!!!
Correlation

Is NOT

Causation
What statistics do we use with
correlations?
   There are many statistics available for
measuring the strength of correlations.

   For this class we will be using pearson
product moment correlation

   Lower-case r represents Pearson Correlation
such that…
The formula:

r=       SP
√SSxSSy
_
Where SS = Σ( X – X )2

And SP = ΣXY - ΣX ΣY     n= number of pairs of scores

n
What do values for r mean?

   r can range from -1 to +1.
   -1 means a perfect negative correlation (as X
increases, Y decreases)
   0 means there is no correlation (no
relationship between X and Y)
   +1 means a perfect positive correlation (as X
increases, Y increases)
Negative Correlation
How Drinking Predicts GPA

4.00
3.50
3.00
2.50
2.00
1.50
1.00
0          2          4            6
Nights Drinking Per Week
Positive Correlation
How SAT Scores Predict

4.00

3.50
3.00
GPA

2.50
2.00
1.50
1.00
400   600   800   1000 1200 1400 1600
SAT Scores
Other pictures of Scatter Plots
Survey research is correlational

   Characteristics of Surveys include:
   Scope can be limited and specific, or broad and
global
   Select a representative sample
   Use predetermined set of questions
Sampling

   Careful selection allows generalizability to
pop.
   *remember, our interest= population
   Biased sample: systematically differs from
the characteristics of the population
   Selection bias: occurs when procedures
used to select a sample results in over/under
representation of some segment(s) of the
population.
Approaches to Sampling

   Nonprobability: does not guarantee that every
element in the population has an equal
chance of being included in the sample
   Convenience sampling
   Probability sampling: allows researcher to
estimate the likelihood that their findings for
the sample differ from those for the
population
   Simple random or stratified random sampling
Survey Methods

   1) MAIL
   Pros: quick, convenient, no interviewer bias, good
for “difficult” topics (anonymous)
   Cons: response bias (not everyone does it)
   Increase return rates by:
   “personal touch”
   Min effort is required
   Intrinsic interest of the topic to the respondent
   Identify w/ researcher or sponsor organization
Survey Methods (cont’d)

   2) Personal interviews
   Pros: more control over administering
   Cons: costly (time/\$), interviewer bias
   How can you improve?
   Hire highly motivated, well paid & trained interviewers
   Give detailed instructions for possible situations
   Close supervision
Survey Methods (cont’d)

   3) Telephone interviews
   Pros: good for brief surveys, less dangerous, no
problem of physical accessibility, or time.
   Cons: response bias, interviewer bias, cell
phones, multiple phone households.
   How would you improve a telephone survey?
Survey Methods (cont’d)

   4) Internet surveys
   Pros: convenient, cheap, large and potentially
diverse or underrepresented samples.
   Cons: selection bias, response bias, lack of
control over the research environment.
   What do you think could be done to improve
internet surveys?
Survey-Research Designs

   1) Cross-sectional: one or more samples drawn AT
ONE TIME from the population.
   Describe and predict
   2) Successive independent samples: same
questions asked of different respondents over a
TIME PERIOD.
   Describe changes in attitude/behavior but not how
   3) Longitudinal: same respondents surveyed over
time in order to look at individuals’ changes
   Hard to identify cause of change
   Threat=Attrition (drop-outs) makes the sample no longer
comparable
Questions

   Demographic variables: describe
characteristics of the people who are
surveyed
   Self-report scales assess
attitudes/preferences
   Accuracy of questionnaires depend on
careful/expert construction
Reliability

   Consistency of the measurement
   If you get on a scale 3 times, do you get the same #?
   Increased by:
   1) using many similar items on a measure
   2) testing a diverse population
   3) using uniform testing procedures
   Test-retest reliability method: give same
questionnaire 2X to large sample.
   Alternate form test
   0.8 reliability needed
Validity

   Construct validity: extent to which it measures the
theoretical construct it’s designed to measure
   Criterion validity: predictive v. concurrent
   Convergent validity: the extent to which 2 similar
measures correlate with each other in the measure
of a theoretical construct (p. 174-5).
   Discriminant validity: extent to which 2 measures do
not correlate with each other in the measurement of
a theoretical construct.
Constructing a Questionnaire

   Wording should be clear & specific. Vocabulary
should be simple & familiar.
should present all conditional info prior to key idea.
Make sure to check for readability.
   Funnel questions: start broad  specific topic
   Filter questions: general questions asked of respondents to
you____? If so, how/why/when/etc?)
   Influence of social desirability: pressure for people to
respond how they “should” believe not as they
actually believe (e.g., perhaps participants will try to
be politically correct).
Why Correlation Causation Does Not
Equal Causation
   Correlation: means 2 variables are related
   We can make predictions based on correlations
   We CANNOT infer cause of the relationship
   “Spurious” relationship: when the relation
between 2 variables can be explained by a
3rd.
Correlation, Causation (cont’d)

   It has been found that
violent crime is
correlated with ice
cream sales (as violent
crime increases, so
does ice cream sales
and vice versa). Why is
this an important
example of correlation
not causation?
Attitudes

In thinking about peoples’ attitudes regarding smoking,
littering, academics, and social honesty, you might
identify the following attitudes:
   Against smoking cigarettes
   Against littering
   For being socially honest

Knowing what you now know about correlation, which do
you think will be related?
Please take out a piece of paper.
Write your name on the back.

Scoring the survey

   Calculate your scores for attitudes towards
smoking (questions 1, 7, 3,10, 5), littering (6,
2, 8, 9, 4,) academic honesty (11, 17, 13, 14,
19) and social honesty (16, 12, 18, 15, 20)
   Assign a 1 to SD, 2 to D, 3 to N, etc.
   Questions marked with R are to be reverse
scored. So 5 to SD, 4 to D, 3 to N, etc. Or
just reverse the Likert scale for questions on
the second half.
   See directions.
Entering Data into SPSS

   Enter titles of the variables into variable view
   For example Smoking, Littering, Academic and
Social
   Enter values for the data in Data View
How to figure out if you want to use an
   Skim the article – Six steps:
   1. Read the abstract. If you want to continue, proceed
to step 2:
   2. Identify the main argument (locate the hypotheses,
see whether or not they were supported and whether
there are implications for future work)
   3. Locate the supporting arguments (transitional
   4. Look for themes – If you see any recurring themes
across articles, these may be important to the area of
research. Keep an eye on how each article
How to figure out if you want to use an
   5. If you’re still unsure as to what the scope of the
paper is, then skim other paragraphs as needed
   6. Decide if you want to keep this article as a potential
article to read “cover to cover.”

   If you’ve determined that an article is worthy of reading
in its entirety, then you’re ready for the next step–
Guidelines for Critically Reading Research Articles

   Take your time! If you rush, you will likely miss important
details. Also, many articles require being read more than once.

   Keep a dictionary nearby – no one knows the definition to
every word, and looking up unknown words will help you to better
understand the material. Don’t own a dictionary? I like
www.yourdictionary.com

   Be a “healthy skeptic” – as you read, thoroughly and carefully
evaluate the claims being presented (e.g., “Is this the best
hypothesis for this question?” “Are these results appropriately
interpreted or is it a stretch?” “Does this idea/theory make
sense?”)
   Write as you read – underline, circle, jot down notes or
questions in the margins or on a separate piece of paper – your
opinion of the article matters! You’ll learn much more if you write
while you read. Also, don’t just underline/highlight. You really
want to be processing the material as you read.
Guidelines for Critically Reading Research Articles
   Introduction – What question is being
study apart from the previous research
reviewed in the intro? Are any key terms
defined? What answers to these authors hope
to find (hypotheses)? Does the literature
review provide acceptable context for the
research questions?
Articles (continued)
   Method – Who participated? How were the
variables of interest operationalized? Is there
a control group? If not, is there an
explanation? Does it make sense?...Were the
participants selected, sampled, randomly
assigned to groups? Do they represent some
larger population of interest? Large enough
n?
Articles (continued)
   Results – Is there evidence that any manipulations
and/or measures worked – what kind of evidence is it?
Were the main hypotheses supported? What were the
main findings? Even if you are unfamiliar with the
statistics used, can you understand the way that
the results of the stats are described? Do the
tables/figures help?
Articles (continued)

   Discussion – In what way(s) does the study add to what we
answered any questions, what were they? Did the study
lead to any new questions – which? What are the practical
implications of the findings? What were the study’s
limitations? What studies should be conducted next? Do
the authors’ implications make sense? Are they
reasonable, or do they stretch the results? How could the
study be improved? What changed would you make?

   Note: These questions are also helpful in writing and revising