EDR-8201 v7

Hannon, B. (2018). Type I error. In B. B. Frey (Ed.), The SAGE encyclopedia of educational research, measurement, and evaluation (pp. 1741-1743). SAGE.
Type I error in hypothesis testing occurs when the null hypothesis is equivocally rejected—in other words, assuming that significant differences exist, when they don’t in fact exist.

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 whether true differences exist.

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 by a researcher and is used to compare to the p-value. This chapter defines and discusses the concepts related to the significance in hypothesis testing.

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.

Leung, J. T., & Shek, D. T. (2018). Quantitative research methods. In B. B. Frey (Ed.), The SAGE encyclopedia of educational research, measurement, and evaluation (pp. 1349-1352). SAGE.
This section describes the concepts of quantitative methods. These are methods that are used to collect and analyze data.

Liu, X.S. (2018). Type II error. In B. B. Frey (Ed.), The SAGE encyclopedia of educational research, measurement, and evaluation (pp. 1743-1745). SAGE.
Type II error in hypothesis testing occurs when the null hypothesis is not rejected when it should be rejected—in other words, assuming that significant differences do not exist, when they do in fact exist.

Seaman, M. (2018). Inferential statistics. In B. B. Frey (Ed.), The SAGE encyclopedia of educational research, measurement, and evaluation (pp. 819-820). SAGE.
This source discusses the importance of inferential statistics and how they are applied to the analysis of observed data from a sample. Furthermore, it explores how the results of the observed data can be applied to make inferences to the general population.