Critical Reading of Research
Find a research article with some type of hypothesis test (ANOVA, single means, paired means). Use a scholarly source (journal article, institutional studies), give the complete citation, and attach the article to your response.
- Discuss the results of the hypothesis test. Comment on the choice of the test statistic.
- Point out anything interesting about the study and explain why you found it interesting. You may comment on the substance (what the researchers found) and/or the methods (how the researchers designed the study).
Book and Note Below
Fox, Levin, & Forde, Elementary Statistics in Criminal Justice Research (4th ed.)
- Chapter 8: Analysis of Variance
Important: In Module 4, you read Chapters 10 and 11 with a view to understanding the concepts and did not focus on how the tests were run in Excel. In this module, we will revert to how we used the Salkind textbook in previous modules. Work in Excel as you read the book, and make sure you understand how to run the tests.
· Salkind, Statistics for People Who (Think They) Hate Statistics: Using Microsoft Excel 2016 (4th ed.)
- Chapter 10: Only the Lonely: The One-Sample Z test
- Chapter 11: t(ea) for Two: Tests Between the Means of Different Groups
- Chapter 12: t(ea) for Two: Tests Between the Means of Related Groups
- Chapter 13: Two Groups Too Many? Try Analysis of Variance
· Hypothesis Testing and ANOVA
· Hypothesis Testing
Now that we understand the theory behind hypothesis testing and how to interpret the results, we will learn how to run the tests. Excel has an entire range of functions you can use to test hypotheses, but it requires that you understand how to set up a hypothesis and make the correct selection of test statistics and other parameters. The lab and readings in this module will help you learn how to run hypothesis tests.
So far, we have learnt how to test for differences between two groups. If we are interested in testing differences between more than two groups, we use a test called the analysis of variance (ANOVA). The ANOVA looks at the distribution of data within a group and also between groups and asks the question: Is there more variation across groups than there is within groups? The ANOVA is set up and interpreted similar to hypothesis tests from previous modules with null and research hypotheses, test statistics, and significance values. The main difference is that the test statistic in this case is the F value. However, the interpretation of results from the test statistics is the same as that from t-tests.
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