Doing Correlational Research Slide 8
Steps in conducting correlational research
•Developing the problem statement
•Measuring the Variables
•Obtaining the Sample
•Analyzing the Data
•Interpreting the Results
Often embedded in larger studies
•As Secondary Analyses
Developing a Problem Statement Slide 9
“What is the relationship between variable X and
variable Y?”
Often want to correlate available demographic variables
with the dependent measures or correlate the various
dependent measures in higher-constraint research
•Useful in detecting confounding variables
•Provides hypotheses for later research
Measuring the Variables Slide 10
Need to use reliable and valid measures
Need to control
•Experimenter expectancy
•Researchers tending to see what they expect to see
•Experimenter reactivity
•Researchers unconsciously influencing participants
•Measurement reactivity
•Participants responding differently because they know they are
being observed
Controlling these effects Slide 11
Experimenter expectancy
•Use objective measures whenever possible
Experimenter reactivity
•Minimize experimenter contact
Measurement reactivity
•Use filler items to distract participants
•Use unobtrusive measures when possible
•Separate the measurements in time
Sampling Considerations Slide 12
Want the sample to be representative
Is the observed relationship the same in each
subpopulation?
•If we suspect such differences, we should compute the
correlation in each subpopulation
•Moderator Variable:
a variable that seems to modify
the relationship between other variables
•e.g., gender: males and females showing different patterns of
relationship between variables
Analyzing the Data Slide 13
Correlations range from -1.00 to +1.00
•Size indicates strength of the relationship
•Sign indicates direction of the relationship
Many types of correlations
•Pearson product-moment correlation
•Spearman rank-order correlation
•Phi
•Advanced techniques (multiple correlation, canonical
correlation, partial correlation, path analysis)
Interpreting the Data Slide 14
Note size and sign of correlation
•Indicates strength and direction of relationship,
respectively
Is the correlation significantly different from zero (i.e.,
evidence for a relationship)?
•Is the p value < alpha?
Coefficient of Determination
•r2 indicates the proportion of variance accounted for
Doing Differential Research Slide 15
Developing the problem statement
Measuring the variables
Selecting appropriate control groups
Obtaining the sample
Analyzing the data
Interpreting the results
Summary Slide 24
Both correlational and differential research involve
measuring the relationship between variables
Drawing causal inferences is risky
Selecting appropriate control groups in the differential
research design can control some, but typically not all,
potential confounding variables

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