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. You will run a Pearson Correlation on them to see if and how they are related to each other. You will need a scatterplot with the line of best fit for each variable pair. Finally, you will run a multiple regression analysis. Fun stuff!!

Each team will create and submit several pptx slides. Slide 1 will contain your correlation information and scatterplots (use EXCEL to create the 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, and the social action scale. You will have 3 correlation coefficients. Use Excel to create the three corresponding scatterplots with the best fit line inserted. Finally, run a multiple regression using these three scale scores. The predicted variable is critical_threat.

Gun Violence:  First, find the correlations between mean scores on: the social concern scale, people_kill, and guns_serious. You will have 3 correlation coefficients. Use Excel to create the three corresponding scatterplots with the best fit line inserted. Finally, run a multiple regression using these three predictors. 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, and the mean scores on the negative beliefs scale. You will have 3 correlation coefficients. Use Excel to create the three corresponding scatterplots with the best fit line inserted. Finally, run a multiple regression using these three scale scores. The predicted variable is scores on the positive belief scale.

Perceptions of discrimination SUU-UT-USA:  First, find the correlations between mean scores on the social concern scale, the total score on the personal experience with discrimination scale, and mean scores on the "discrimination is serious in the United States" scale. You will have 3 correlation coefficients. Use Excel to create the three corresponding scatterplots with the best fit line inserted. Finally, run a multiple regression using these three predictors. 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, and the total scores on the familiarity scale. You will have 3 correlation coefficients. Use Excel to create the three corresponding scatterplots with the best fit line inserted. Finally, run a multiple regression using these predictors. The predicted variable is scores on the new variable "Transpeople_discrimination". To get this new variable, simply calculate the mean of Transmen_discrimination and Transwomen_discrimination.

COVID vaccines and other mandates:  First, find the correlations between means scores on: the social concern scale, the vaccine myth scale, and the COVID myth scale. You will have 3 correlation coefficients. Use Excel to create the three corresponding scatterplots with the best fit line inserted. Finally, run a multiple regression using these three scales. The predicted variable is scores on the Restriction Support scale.