# PSYC 2040 Chapter Notes - Chapter 5: Lincoln Near-Earth Asteroid Research, Null Hypothesis, Repeated Measures Design

by OC766356

School

University of GuelphDepartment

PsychologyCourse Code

PSYC 2040Professor

Naseem Al- AidroosChapter

5This

**preview**shows half of the first page. to view the full**3 pages of the document.**Chapter #5 Completely Randomized Factorial Designs

When researchers want to investigate the eects of more than one

independent variable on a dependent variable.

CRF design is a form of analysis of variance that permits a

researcher to investigate the eects of two or more factors and

to assess any possible interactions between these factors

The primary characteristic of this type of design is that each cell

in the design is made up of a random sample of observations

Thus, in a two factor (AB) design, there are AXB groups of

observations and the researcher can assess the eects of the A

factor, the B factor and the combination of A and B factors

In a three factor design, there are axbxc random samples of

observations and the researcher can investigate the eects of A,

B, and C by themselves, the two way interactions of AB, Ac, and

BC and the three way interaction of ABC

In theory this can be extended to any # of factors

SPSS is limited to 5

This design is more complex than single factor analysis of

variance

CRF is sometimes described as two or more single factor designs

in the same study

It permits the researcher to determine whether or not dierences

that can be attributed to one of the factors are consistent at all

levels of the other factor(s) –i.e., whether or not the two (or

more) factors interact with one another to produce eects that

could not be determined if the factors were investigated one at a

time

KEY CONCEPTS

1 DV

2+ IV(s) and each needs to have 2 or more levels

Not repeated measures

Conducting a CRF is dierent from conducting two ONE WAY ANOVAs

because:

There’s more than one independent variable

Interaction between two independent variables

POSSIBILITY FOR INTERACTION

Main Eects: Overall eect of that variable ignoring all other variables

**marginal

Simple Main Eects: compare cell means and the interaction in this

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