LibGuides: EDR-8202 v5: Week 5 Resources

Week 5 Resources

divorce-studentversion.sav
You will use this data file to complete this week’s assignment.

Stats II Week 5 ANCOVA
Booker-Zorigan, B. (2021, August 7). Stats II Week 5 ANCOVA [Video]. Kaltura.
This video presents an overview of the Week 5 assignment, including a walkthrough of ANCOVA.
Stats II Week 5 ANOVA
Booker-Zorigan, B. (2021, August 7). Stats II Week 5 ANOVA [Video]. Kaltura.
This video presents an overview of the Week 5 assignment, including a walkthrough of ANOVA.
Stats II Week 5 MANOVA
Booker-Zorigan, B. (2021, August 7). Stats II Week 5 MANOVA [Video]. Kaltura.
This video presents an overview of the Week 5 assignment, including a walkthrough of MANOVA.

Discovering Statistics Using IBM SPSS Statistics by Andy Field
ISBN: 9781526419521
Publication Date: 2018-01-08
Chapter 12 (pp. 385-422) will discuss issues specific for comparing several means, or ANOVA. Among the topics included are, assumptions of the test, post hoc procedures, effect size, etc.
This is a Redshelf book which you will access through the Bookshelf on the top navigation bar in the course.

Eta squared
Fritz, C. O., & Morris, P. E. (2018). Eta squared. In B. B. Frey (Ed.), The SAGE encyclopedia of educational research, measurement, and evaluation (pp. 607). SAGE.
Eta squared is a measure of effect size estimate. It is very often used in the analysis of variance (ANOVA).
F distribution.
Raunig, D. (2018). F distribution. In B. B. Frey (Ed.), The SAGE encyclopedia of educational research, measurement, and evaluation (pp. 659-662). SAGE. 10.4135/9781506326139
The F distribution is very important because it is related to the ANOVA. The F distribution is the most powerful analysis to compare two variances.
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.
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.
This resource was introduced in a previous week. Hypotheses are formed in inferential statistics and used to make decisions about the population using a sample. This source provides discussion regarding the decisions that are made based on hypothesis testing.
Interaction
Fritz, C. O., & Morris, P. E. (2018). Interaction. In B. B. Frey (Ed.), The SAGE encyclopedia of educational research, measurement, and evaluation (pp. 849-853). SAGE.
This section explains how to interpret the effect of two or more independent variables in a dependent variable. Interaction is occurring when the effect of one variable changes depending on the value of another variable.
Multivariate analysis of variance. Methods of Multivariate Analysis
Rencher, A., & Christensen, W. (2012). Multivariate analysis of variance. Methods of Multivariate Analysis (pp. 169-244). Hoboken, NJ: Wiley & Sons.
This is an extension of a univariate analysis of variance. In this case, you measure more than one dependent variable with each independent variable..
Multivariate analysis of variance
Stockburger, D. (2018). Multivariate analysis of variance. In B. B. Frey (Ed.), The SAGE encyclopedia of educational research, measurement, and evaluation (pp. 1120 - 1126). SAGE.
This is another reference that discusses MANOVA, which is an extension of a univariate analysis of variance. In this case, you measure more than one dependent variable with each independent variable.
Post hoc analysis.
Tipton, R., & Morgan, G. (2018). Post hoc analysis. In B. B. Frey (Ed.), The SAGE encyclopedia of educational research, measurement, and evaluation (pp. 1271-1273). SAGE.
These analyses are conducted after the rejection of the null hypothesis. They are used to examine mean differences. This section provides an overview of these tests used in the ANOVA.
One way between subject ANOVA
Meyers, L. S., Gamst, G. C., & Guarino, A. J. (2013). One way between subject ANOVA (pp. 477 - 484). In Performing data analysis using IBM SPSS. Wiley & Sons. <.br> This source describes the procedures to conduct a one-way ANOVA using SPSS. Furthermore, it provides explanations of the different outputs obtained in the analysis.
Two-Way Analysis of Variance
Harring, J., & Johnson, T. (2018). Two-way analysis of variance. In B. Frey (Ed.), The SAGE encyclopedia of educational research, measurement, and evaluation (Vol. 1, pp. 1734-1737). SAGE Publications, Inc.
This test is an extension of ANOVA. In this case, you are testing the effect of two independent variables on a dependent variable. In addition, the interaction between both variables will be examined.
Two way between subject ANOVA
Meyers, L. S., Gamst, G. C., & Guarino, A. J. (2013). Two way between subject ANOVA (pp. 507 - 520). In Performing data analysis using IBM SPSS. Wiley & Sons.
This source describes the procedures to conduct a two-way ANOVA using SPSS. Furthermore, it provides explanations of the different outputs obtained in the analysis.

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.
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.
Type I error
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 in fact they don’t exist.
Type II error.
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.
As you learned from this resource in a previous week, Type II error in hypothesis testing occurs when the null hypothesis is equivocally not rejected—in other words, assuming that significant differences do not exist, when they do in fact exist.
Effect size.
Fritz, C. O., & Morris, P. E. (2018). Effect size. In B. B. Frey (Ed.), The SAGE encyclopedia of educational research, measurement, and evaluation (pp. 577-578). SAGE.
This section describes the different measures of effect size used in statistics. These effects are important in terms of the size and the possibility of being observed in further studies where the sample is obtained from the same population.
Results section
Zheng, C. (2018). Results section. In B. B. Frey (Ed.), The SAGE encyclopedia of educational research, measurement, and evaluation (pp. 1432). SAGE.
This resource describes the research paper section that includes the results of the statistical analysis. The results section is very important in the research paper because provides the answer to the research questions.
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.

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