Team Project Assignments

Statistics Lab

1

5

1 way ANOVA

Submit after you review your feedback from SPSS assignment 7.

 

Each team will run a one-way ANOVA - independent or repeated as appropriate - on the variables I tell them to. Scroll to the end of this page to find out what your team's analysis will be.

 

Each team will create and submit two pptx slides: one slide for their ANOVA, post hoc test information (if needed), and EXCEL graph. The other slide will include the relevant SPSS output with the numbers used hi-lighted. Make sure you include the SPSS output showing the means and SEMs used in your graph, and not just the Levene's test, ANOVA, and post hoc test results.

 

On the ANOVA slide, you are asked to report the statistical results in correct APA format. This is illustrated below:

 

(df,df) = actual value for F, = the sig. value

 

e.g.  F(3,36) = 4.43, p = .043   Note that F and p are italicized. Also, you can choose between reporting the actual sig. value, p >.05 or p<.05 as appropriate and whichever will look more impressive. Remember our discussion in class about this?

 

Please see this sample pptx for what goes on the ANOVA slide.

The video library has a clip on how to add SEMs (also called y-error bars) to graphs.

 

FINALLY, add one more slide. Include the names of all the team members and whether they were present for the meeting. If present, indicate whether they were contributory or not.

 

Please let me know if you have any questions!

Military Tough: Do sex and video combined have an effect on pain scores? To answer this, you will have to do the following: 1. create a new variable in variable view (sex_video_combo). 2.  code the categories (male_action, male_military, female_action, female_military) 3. in data view, assign each participant a number code (1,2,3,4) for this variable, depending on which code describes them. 4. run the ANOVA

Emotionally Intelligent:  Do sex and HD combined have an effect on emotional IQ scores? To answer this, you will have to do the following: 1. create a new variable in variable view (sex_HD). 2.  code the categories (male_right, male_left, female_right, female_left) 3. in data view, assign each participant a number code (1,2,3,4) for this variable, depending on which code describes them. 4. run the ANOVA

 

Yuck! That's Gross: Do sex and political ideology (PI) combined have any effect on reach in time? To answer this, you will do the following: 1. use "transform" then "recode into different variables" to create two categories of political ideology. Anyone who scores 1-5 label conservative. Anyone who scores 6-9 label liberal. Use this video to show you how. 2. create a new variable in variable view (sex_PI). 3.  code the categories (male_conservative, male_liberal, female_conservative, female_liberal) 4. in data view, assign each participant a number code (1,2,3,4) for this variable, depending on which code describes them. 5. run the ANOVA 

In the Eyes of the Beholder:  Do sex of the model and the background color of the photograph combined have any effect on the perceived attractiveness of the model? To answer this, you will have to do the following: 1. create a new variable in variable view (sex_color). 2.  code the categories (male_red, male_white, male_black, female_red, female_white, female_black) 3. in data view, assign each participant a number code (1,2,3,4,5,6) for this variable, depending on which code describes them. 4. run the ANOVA

 

Lost in Space: Do sex and HD combined have an effect on time to rotate an object in space? To answer this, you will have to do the following: 1. create a new variable in variable view (sex_HD). 2.  code the categories (male_right, male_left, female_right, female_left) 3. in data view, assign each participant a number code (1,2,3,4) for this variable, depending on which code describes them. 4. run the ANOVA

 

Hairy Faces:  Do sex and face (hairy vs clean) combined have an effect on perceived IQ? To answer this, you will have to do the following: 1. create a new variable in variable view (sex_face). 2.  code the categories (male_clean, male_hairy, female_clean, female_hairy) 3. in data view, assign each participant a number code (1,2,3,4) for this variable, depending on which code describes them. 4. run the ANOVA