Chapter 18 Some Other (Important) Statistical Procedures You Should Know About

Part IVSignificantly Different:

Using Inferential Statistics

Multivariate Analysis of Variance (MANOVA)

Used when there is more than one dependent variable

Allows you to determine the best combination of dependent variables.Example: Adolescent Coping Scale

Five Subscales of interestEffects of Gender, Race and Grade for each of the

five scales

Repeated Measures Analysis of Variance

Participants are tested on a variable more than onceExample: Monthly spelling tests

Examining student performance over timeHow is this different from a dependent

samples t-test?Your scores on Quests 1-4

Analysis of Covariance

Allows you to equalize initial differences between groups

Especially useful when you want to “control” for a variable that might confound your results

Effects of study time and sleep on test results.What about prior abilities in the subject

matter?

Multiple Regression

You learned this in Chapter 15…

Used when you have more than one predictor variableThe BIG rules of multiple predictors…IVs should be correlated with the DVBUT IVs should not be correlated with each

other…you want “unique” contributions

Factor Analysis

Based on how well items are related to one anotherFactors

Each factor represents several variablesMore efficient means of representing data

that relate to each other on some theoretical construct

Path Analysis

Examines the direction of relationships between variablesCausality

Examines the direction and strength of relationships

Typically uses correlation coefficients to show the strengths of the relationships between the variables.