**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.**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.**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.

**Supplemental Resources**

**Academic Success Center (ASC). (2020).***Statistics resources*. National 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.****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.****Hypothesis testing****Coleman, J. S. (2018). Hypothesis testing. In B. B. Frey (Ed.), The SAGE encyclopedia of educational research, measurement, and evaluation (pp. 803-804). SAGE.****Hypothesis testing is the main method used in statistics to examine statistical inference. The researcher set a hypothesis (supposition) about a population parameter. In statistics, the hypothesis that is always tested is the null hypothesis.***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.**Robust statistics****Blaine, B. E. (2018). Robust statistics. In B. B. Frey (Ed.), The SAGE encyclopedia of educational research, measurement, and evaluation (pp. 1435-1436). SAGE.**

This source defines and discusses the concept of robust statistics. These are procedures for which, in spite of a violation to the assumptions in statistics, the results can still be accepted as accurate results.**Levene’s homogeneity of variance test.****Chen, Y. H., Wang, Y., & Kromrey, J. (2018). Levene’s homogeneity of variance test. In B. B. Frey (Ed.),***The SAGE encyclopedia of educational research, measurement, and evaluation*(pp. 970-972). SAGE.

The Levene’s test is a test to examine the assumption of homogeneity of variance. This assumption is used in the independent*t*- test analysis and the analysis of variance.**Normal distribution.****Nicol, A. A. M. (2022). Normal distribution. In B. B. Frey (Ed.),***The SAGE encyclopedia of educational research, measurement, and evaluation*(pp. 1088-1091). SAGE..*R*^{2}.**Taraday, M., & Wieczorek-Taraday, A. (2018).***R*^{2}. 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*R*^{2}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.**Simple linear regression.****Lawrence S. Meyers, , Glenn C. Gamst, , and A. J. Guarino. (2013). Simple linear regression. In B. B. Frey (Ed.), Performing Data Analysis Using IBM SPSS (pp. 1517-1519). Wiley.**

Simple linear regression is the simplest form of prediction. In this section, you will learn that the correlation analysis is related to a regression analysis. However, correlations are used to examine relationships, while regression analyses are used to for prediction.**Exploratory factor analysis****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**

Exploratory factor analysis is used to determine the items in a survey that are related to each other, and it is used to develop constructs or factors within the survey.

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