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