.4 SPSS Activity: Calculating and Interpreting Results for a Two-Way Between-Subjects Factorial ANOVA (2x3 design).

Activity 7.4 Instructions Document

Name: 7.4 SPSS Activity: Calculating and Interpreting Results for a Two-Way Between-Subjects

Factorial ANOVA (2x3 design).

The following activity will present an opportunity to put into practice what you have learned and read

about regarding Two-Way Between-Subjects Factorial ANOVA. The narratives supplied in these

exercises will provide all the information you will need to determine what main effects and interactions

are to be analyzed. Please read the following narrative and then use the Excel spreadsheet provided to

import the data into SPSS to construct a dataset that SPSS can use to perform the proper calculations and

post hoc analyses.

Problem Narrative 7.4:

A researcher doing research on performance in virtual environments wants to find out if gender plays a

role in manipulation of controls in a virtual environment. The researcher wants to determine if it is

worthwhile designing virtual interfaces with specific differences based on research that indicates that

male and female participants perform differently depending on the size of buttons provided in a virtual

interface. To investigate this idea, the researcher has designed an experiment that uses the same virtual

interface except that the control buttons that operate equipment within the virtual environment are 3

different sizes: 1 cm, 2 cm, and 3 cm size buttons. The design is a 2x3 factorial design with 6 conditions

overall. The researcher plans to recruit 30 male participants and 30 female participants and randomly

assign 10 different males to test each size button, and 10 different females to test each size button. Each

participant will be run through 100 trials and the data recorded will document the number of times the

participant accurately responded to a random number generator display with the correct button push in the

virtual environment. The number of times the participant is able to respond correctly is recorded and

labeled "accuracy score".

To analyze the data, a two-way between-subjects 2x3 factorial ANOVA will be used to analyze the main

effects of gender and button size on accuracy score performance. The interaction of gender and button

size will also be analyzed for accuracy score performance. The accuracy score performance scores range

from 0 - 100 with larger scores indicating better accuracy. The hypothesis is that males and females will

perform differently depending on the size of the virtual buttons, and that there will be an interaction

between gender and button size.

Download the Excel spreadsheet “7.4 Data Input” and import the spreadsheet into SPSS for subsequent

analyses

Part I: Import Data into SPSS:

Use the spreadsheet you just downloaded “7.4 Data Input” and import the data in this spreadsheet into

SPSS for subsequent analyses. Name your SPSS data file “7.4 SPSS Gender Performance Dataset”

with the “.sav” extension. Your SPSS data file should be ready to use for analysis.

Part II: Short Answer Questions:

Create an MSWord document to answer the short answer questions from part II and III of this exercise.

The name of the file will be “7.4 SPSS Exercise – Short Answer Questions”. Save this for subsequent

upload as one of your deliverables for this exercise.

Answer the following based on the narrative and data provided:

1. What are the dependent and independent variables in this scenario?

2. How many levels of each independent variable are there? Name/list them?

3. What interaction can be examined and what post hoc test will you use to examine the interactions

for significance?

4. What is the hypothesis?

5. What does it mean if you have a significant interaction between the variables being examined?

6. What does it mean if you do not find any significant interactions between the variables being

examined?

Part III: Running the Appropriate Analysis in SPSS:

Using the “7.4 SPSS Gender Performance Dataset” you created previously in this exercise, run the

appropriate ANOVA (F test) in SPSS. When running a GLM Univariate ANOVA, make sure you include

a means plot, a LSD Post Hoc Analysis, Display Means for Overall and your display type variable, and

make sure you check off the boxes for Compare main effects, Descriptive Statistics, Estimates of effect

size, and observed power.

Add the following to your list of short answer questions as information obtained from your SPSS output

file.

7. What are your numerical results? Make sure to report your results in proper APA format (i.e.

F(dfBG, dfE) = Fcalc, p= x.xx).

8. Did you find any significant results (main effects or interactions?)

Save the GLM ANOVA output as “7.4 SPSS Gender Performance Output” as an “.spv” file to upload

as a deliverable at the conclusion of this exercise.

Part IV: Results Write Up:

Write up the results of your data analysis in standard APA format being sure to mention all relevant

variables and findings in your write up. Make sure your format adheres to APA format and guidelines.

Save the document as “7.4 SPSS Results Write Up”.

(If you have questions about what a complete results write up for an ANOVA looks like, either look up

conference and journal articles that use t-tests as their statistical analysis, or contact your instructor for

specific guidance.)

Your deliverables for this SPSS exercise will be:

1. The IBM SPSS data file “7.4 SPSS Gender Performance Dataset”.

2. The IBM SPSS viewer file “7.4 SPSS Gender Performance Output”.

3. The Short Answer document “7.4 SPSS Exercise – Short Answer Questions”.

4. The APA formatted results write up “7.4 SPSS Results Write Up”.

Upload all four of these files as your submission for this exercise to be considered for full credit.