**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 only main text reading for this week. These chapters (Ch. 10, 15) discuss MANOVA and ANCOVA, and repeated measures procedures. **

**Laerd Statistics**Laerd. (2018).*Two-way ANOVA in SPSS Statistics.*Lund Research Ltd.

**Laerd is a great statistics site and this page discusses multiple regression analysis.****Covariance**Sim, J. (2018). Analysis of Covariance. In B. B. Frey (Ed.),*The SAGE encyclopedia of educational research, measurement, and evaluation*(pp. 82 - 85). SAGE.

**This is a combination of ANOVA and linear regression. In this case, you can use a variable that is related to the outcome variable and control for its effects. This is the covariate.****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.

**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.**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.****Interaction**Fritz, C. & Morris, P. (2018). Interaction. In B. B. Frey (Ed.),*The SAGE encyclopedia of educational research, measurement, and evaluation*(pp. 849-853). SAGE.

**This resource 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.****MANOVA**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**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 resource provides an overview of these tests used in the ANOVA.****Two-way ANOVA**Harring, J. & Johnson, T. (2018). Two-way analysis of variance. In B. B. Frey (Ed.),*The SAGE encyclopedia of educational research, measurement, and evaluation*(pp. 1734 - 1737). SAGE.

**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.****Covariance and Multivariate**Harrison, V., Kemp, R., Brace, N., & Snelgar, R. (2020). Analysis of covariance and multivariate analysis of variance.*In SPSS for Psychologists, Chapter 11.*Bloomsbury Publishing Plc.

**This chapter discusses Analysis of covariance and multivariate analysis of variance for SPSS.****One-Way ANOVA Repeated Measures Test and Friedman Test**Aldrich, J.O. (2019). One-way ANOVA repeated measures test and Friedman test. In Using IBM® SPSS® Statistics: An*Interactive Hands-On Approach*(3rd ed.; Vols. 1-0). SAGE Publications. Inc. https://doi.org/10.4135/9781544318912

**This resource goes over conducting one-way ANOVA repeated measures test and Friedman test.****Factorial Analysis of Variance**Harrison, V., Kemp, R., Brace, N., & Snelgar, R. (2020). Factorial analysis of variance. In*SPSS for Psychologists*, Chapter 11. Bloomsbury Publishing Plc.

**This chapter discusses factorial analysis of variance for SPSS.****Two-Way ANOVA (Factorial**Aldrich, J.O. (2019). Two-way ANOVA (factorial). In Using IBM® SPSS® Statistics: An*Interactive Hands-On Approach*(3rd ed.; Vols. 1-0). SAGE Publications. Inc. https://doi.org/10.4135/9781544318912

**This resource goes over conducting Two-Way ANOVA (Factorial).**

**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.****Levene's**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. http://dx.doi.org.proxy1.ncu.edu/10.4135/9781506326139.n392

**Introduced in previous weeks, this resource reminds you that 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 ANOVA.****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.

**As you learned in previous weeks, 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.****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 last 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 resource, introduced previously, 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, introduced in Week 3, 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.**

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