COMM 1 Lecture Notes - Lecture 9: Partial Correlation, Longitudinal Study, Random Assignment

• School: Irvine Valley College
• Department: Communication Studies
• Course: COMM 1
• Professor: Rybold

Document Summary

Depends on your hypothesis/research question, and how your variables are measured! Cannot conclude that one variable causes the other. Variables must be related (x correlated with y) Okay so far - surveys can show that. E. g. increase in studying, increase in gpa. So, survey/correlational research has two causality problems. To help solve the third variable problem: Time 1: measure x & y variables. Time 1: measure x & y variables again later for the same people. Compute r"s for x & y but across the times measured. So, measure both variables for same people at different times; then see which cross relationship holds. Purpose to test hypotheses of cause and effect. Manipulation of causal variables, while controlling all other variables. Compare measures (e. g. , mean scores) across conditions and see if a difference exists. Helps protect against the attitudes that people have coming in to the study. Everyone must have an equal chance of ending up in either condition.