## Connecting students to knowledge

and its application

##

Southern Utah University

Lynn White, Ph.D.

Team Project Assignments

## Statistics Lab

## 1

## correlation & regression

Submit after you review your feedback from SPSS assignment 10.

At the bottom of this page, you will see which continuous interval/ratio variables I want your team to correlate and run a multiple regression on. You will need to run these analyses for the SOLO ANALYSIS. You do not need to create the scatterplots for the solo analysis. Do not forget to complete this and upload the results the day BEFORE the lab. If you forgot how to run correlations and regressions, watch lab lecture 11. For a "quick an easy" method of finding correlations, see the video on this page.

IN THE LAB: You will compare your answers with your teammates. Once the correct answers have been verified, you will use Excel to create three scatterplots as directed below.

Each team will then create and submit several pptx slides. Slide 1 will contain your correlation information and scatterplots. Slide 2 will have the relevant SPSS output on it with the numbers used hi-lighted. Slide 3 will have a table to show the results of the regression. Slide 4 will contain the relevant SPSS output with the numbers used hi-lighted. Be sure to report the statistical results in correct APA statistical notation format. Please see this sample pptx for what goes on the correlation and multple regression slides

Please let me know if you have any questions!

I have created a video to show you how to create a scatterplot using Excel. It does not show you how to insert the best fitting line. To do this, click on the graph. You will see a "+" sign in the upper right corner. Click on it and you will see a list of chart elements. Select "trendline" to insert the best fitting line.

Climate Change: First, find the correlations between mean scores on: the social concern scale, the personal action scale, the social action scale, and the belief that climate change is a critical threat to life as we know it. See the "fast and easy" video above. You will have 6 correlation coefficients. Use Excel to create three scatterplots with the best fit line inserted. 1. social concern (x) and critical threat (y) 2. social action (x) and critical threat (y) 3. personal action (x) and critical threat (y). Finally, run a multiple regression using the scale scores that are SIGNIFICANTLY correlated with critical threat. The predicted variable is critical threat.

Gun Violence: First, find the correlations between mean scores on: the social concern scale, people kill, guns serious, and restriction support. See the "fast and easy" video above. You will have 6 correlation coefficients. Use Excel to create three scatterplots with the best fit line inserted. 1. social concern scale (x) and restriction support (y) 2. people kill (x) and restriction support (y) 3. guns serious (x) and restriction support (y). Finally, run a multiple regression using the variables that SIGNIFICANTLY correlated with restriction support. The predicted variable is scores on the restriction support scale.

American Immigrants: First, find the correlations between mean scores on the social concern scale, the total score on the personal experience with discrimination scale, the mean scores on the negative beliefs scale, and mean scores on the positive belief scale. See the "fast and easy" video above. You will have 6 correlation coefficients. Use Excel to create three scatterplots with the best fit line inserted. 1. social concern scale (x) and positive belief scale (y) 2. personal experience with discrimination (x) and positive belief scale (y) 3. negative belief scale (x) and positive belief scale (y). Finally, run a multiple regression using the variables that SIGNIFICANTLY correlated with positive beliefs. The predicted variable is scores on the positive belief scale.

Discrimination everywhere except my backyard: First, find the correlations between mean scores on the social concern scale, the total score on the personal experience with discrimination scale, mean scores on the "discrimination is serious in the United States" scale, and mean scores on the "discrimination is serious at SUU" scale. See the "fast and easy" video above. You will have 6 correlation coefficients. Use Excel to create three scatterplots with the best fit line inserted. 1. social concern (x) and discrimination is serious at SUU (y) 2. personal experience with discrimination (x) and discrimination is serious at SUU (y) 3. discrimination is serious in the United States (x) and discrimination is serious at SUU (y). Finally, run a multiple regression using the variables that SIGNIFICANTLY correlated with discrimination is serious at SUU. The predicted variable is scores on the "discrimination is serious at SUU" scale.

Transgender discrimination: First, find the correlations between mean scores on the social concern scale, the total scores on the personal experience with discrimination scale, the total scores on the trans familiarity scale, and the total scores on the trans freedom (TFree) scale. See the "fast and easy" video above. You will have 6 correlation coefficients. Use Excel to create three scatterplots with the best fit line inserted. 1. social concern (x) and TFree (y) 2. personal experience with discrimination (x) and TFree (y) 3. trans familiarity (x) and TFree (y). Finally, run a multiple regression using the variables that SIGNIFICANTLY correlated with TFree. The predicted variable is scores on the Trans Freedom scale.

COVID vaccine myths and mandates: First, find the correlations between means scores on: the social concern scale, the vaccine myth scale, the COVID myth scale, and the restriction support scale. See the "fast and easy" video above. You will have 6 correlation coefficients. Use Excel to create three scatterplots with the best fit line inserted. 1. social concern (x) and restriction support (y) 2. belief in vaccine myths (x) and restriction support (y) 3. belief in COVID myths (x) and restriction support (y). Finally, run a multiple regression the variables that SIGNIFICANTLY correlated with restriction support. The predicted variable is scores on the restriction support scale.