**Using Statistics in the Social and Health Sciences with SPSS and Excel**Abbott, M. (2017).*Using statistics in the social health sciences with SPSS and Excel.*Wiley & Sons.

**This is the first main text reading for this week. This chapter (Ch. 13) discusses multiple linear regression. **

**IBM SPSS Essentials: Managing and Analyzing Social Sciences Data**Kulas, J., Roji, R., & Smith, A. (2021).*IBM SPSS essentials: Managing and analyzing Social Sciences data.*John Wiley & Sons Inc.

**This is the second main text reading for this week. This chapter (Ch. 11 pp. 125-140) multiple and hierarchical regression. **

**Laerd Statistics**Laerd. (2018).*Multiple regression analysis using SPSS Statistics.*Lund Research Ltd.

**Laerd is a great statistics site and this page discusses multiple regression analysis.****Correlation**Jung, H. J., & Randall, J. (2018). Correlation. In B. B. Frey (Ed.),*The SAGE encyclopedia of educational research, measurement, and evaluation*(pp. 413). SAGE.

**Correlation is used to examine the relationship between variables. This relationship can be quantified by calculating the correlation coefficient.****Multicollinearity**Nimon, K. (2018). Multicollinearity. In B. B. Frey (Ed.),*The SAGE encyclopedia of educational research, measurement, and evaluation*(p. 1100). SAGE.

**Multicollinearity refers to the relationship between predictors in a multiple regression analysis. If two or more predictors are highly correlated to each other, the researcher must determine which one of them is going to be included in the mode. Example of theory that holds true if there is no multicollinearity.****Multicollinearity**Daoud, J.I. (2017). Multicollinearity and regression analysis.*Journal of Physics: Conference Series, 949*(1), 1.

**Multicollinearity refers to the relationship between predictors in a multiple regression analysis. If two or more predictors are highly correlated to each other, the researcher must determine which one of them is going to be included in the mode. Definition of Multicollinearity itself.****Multiple Linear Regression**Sims, J. (2018). Multiple linear regression. In B. B. Frey (Ed.),*The SAGE encyclopedia of educational research, measurement, and evaluation*(pp. 1111-1113). SAGE.

**Multiple linear regression is an extension of the simple linear regression. In this case, the researcher is building a prediction model with more than one predictor. The model determines the amount of contribution that a predictor has on the predicted variable.****Pearson Correlation Coefficient**Gordon, M., & Courtney, R. (2018). Pearson correlation coefficient. In B. B. Frey (Ed.),*The SAGE encyclopedia of educational research, measurement, and evaluation*(pp. 1299-1233). SAGE.

**The Pearson correlation is used to examine the linear relationship between two variables. It is a measure that is used when both variables are continuous.**

**ASC Statistics Resources**Academic Success Center (ASC). (2024).*Statistics resources.*Northcentral University.

**This page in the ASC includes all of the statistics resources curated by NU's Academic Success Center. Use the headings on the left side of this ASC page to navigate to your particular area of need.****APA Formatting Guide for Statistics**American Psychological Association. (2022).*American Psychological Association Style (7th ed.) numbers and statistics guide.*American Psychological Association. https://doi.org/10.1037/0000165-000

**This resource gives a summary of how to format statistics in APA 7th edition formatting.****Presenting Statistics in Text**Academic Success Center (ASC). (2024).*Presenting statistics in text.*Northcentral University.

**This page from the ASC offers support on how to use appropriately the different elements of statistics within text for reports, papers, assignments, etc.**

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