LibGuides: EDR-8202 v5: Week 4 Resources

Week 4 Resources

Supermodel.sav
You will use this data file to complete this week’s assignment.

Stats II Week 4 Multiple Regression
Booker-Zorigan, B. (2021, August 7). Stats II Week 4 Multiple Regression. [Video] Kaltura.
This video presents a walkthrough of the Week 4 assignment, including an overview of how to complete a multiple regression.
Analysis of variance.
Boone, E. L. (2018). Analysis of variance. In B. B. Frey (Ed.), The SAGE encyclopedia of educational research, measurement, and evaluation (pp. 87-89). SAGE.
When comparing differences between three groups or more, one of the most common analyses is the analysis of variance (ANOVA). This resource provides a thorough explanation of this parametric technique.
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
Daoud, J. I. (2017). Multicollinearity and regression analysis. J. Phys.: Conf. Ser. 949, 012009. 10.1088/1742-6596/949/1/012009
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.
Multiple linear regression
Frey, B. (2018). The SAGE encyclopedia of educational research, measurement, and evaluation (Vols. 1-4). Thousand Oaks,, CA: SAGE Publications, Inc. doi: 10.4135/9781506326139
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.
Pearson correlation
Meyers, L. S., Gamst, G. C., & Guarino, A. J. (2013). Pearson correlation (pp. 159 - 164). In Performing data analysis using IBM SPSS. Wiley & Sons.
This source describes the procedures to conduct the Pearson correlation using SPSS. Furthermore, it provides explanations of the different outputs obtained in the analysis.

Supplemental Resources

ASC Statistics Resources
Academic Success Center (ASC). (2020). Statistics resources. Northcentral University.
This LibGuide 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.
Alpha level.
Kim, H. W. (2018). Alpha level. In B. B. Frey (Ed.), The SAGE encyclopedia of educational research, measurement, and evaluation (pp. 65-66). SAGE.
The alpha level is chosen a priori as a level (typically .05) used to reject or not reject the null hypothesis, and this value is compared to p - value obtained from the statistical analysis. This chapter defines and discusses the concepts related to the alpha level.
p Value
Kim, H. W. (2018). p Value. In B. B. Frey (Ed.), The SAGE encyclopedia of educational research, measurement, and evaluation (pp. 1195-1198). SAGE.
The p - value is the probability value that is used in conjunction with the concept of significance. This chapter discusses the different uses of the p - value.
Significance
Harlow, L. (2018). Significance. In B. B. Frey (Ed.), The SAGE encyclopedia of educational research, measurement, and evaluation (pp. 1514-1516). SAGE.
The author of these pages presents the concept of significance in statistics. Significance indicates the probability of an event (e.g., the difference between two groups) happening by chance—or that true differences exist.
R².
Taraday, M., & Wieczorek-Taraday, A. (2018). R². In B. B. Frey (Ed.), The SAGE encyclopedia of educational research, measurement, and evaluation (pp. 1362-1363). SAGE.
This is the coefficient of determination used in a regression analysis. The R² is used to represent that amount of variance in the dependent variable, which is predicted by the independent variable.
Scatterplots.
LeBeau, B. (2018). Scatterplots. In B. B. Frey (Ed.), The SAGE encyclopedia of educational research, measurement, and evaluation (pp. 1456-1460). SAGE.
This source presents scatterplots. These are graphical representations that are used in statistics to examine the relationships between variables.
Presenting Statistics in Text
This page from the ASC offers support on how to use appropriately the different elements of statistics within text that you write.