PSC 41 Lecture Notes - Lecture 17: Analysis Of Variance, Statistical Significance, Null Hypothesis

• School: UC-Davis
• Department: Psychology
• Course: PSC 41
• Professor: Cross, Victoria

Document Summary

If the study was repeated we would expect the same results. The results found were not due to chance. Therefore, if we repeated the study we would/would not expect to find the same results. If you have more than two groups, a t-test won"t work! An anova allows you to compare: predictor variable with more than two levels, more than one predictor variable. This calculates statistical significance for the main effects of each variable plus all possible interactions. Measure a relationship between variables: look at relative position of each participant on two continuous variables. Calculate a single number that quantifies that relationship (r): r is a number between -1 and 1. Negative correlation: as one increases, the other decreases. Positive correlation: they both increase or decrease together. Nature of the relationship: positive or negative. Strength of the relationship: how closely the scores cluster around the line that has the best fit with the data.