Reference Material

  • There are more than a dozen different fit statistics researchers use to assess their confirmatory factor analyses and structural equation models. Here we have assembled a list of the most popular fit statistics used and recommended cut-offs that indicate a good fit. 

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  • This handout lists the most commonly used effect sizes, adjustments, and rules of thumb concerning sample size calculation. 

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  • These cheat sheets make it easy to learn about and use some of the favorite packages of RStudio. 

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  • This site is a description of the mathematics behind survival analysis. It starts with a definition of the survival function. Then it discusses estimating the survival function with the Kaplan-Meier curve.  Then it discusses comparing survival curves. Finally, there is a discussion of Cox Proportional Hazards regression analysis.

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  • Resource that gives a clear description of what the p-values and significance levels mean, and what statistical significance means. Graphs are used to illustrate the topics covered in this source.
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  • Text resource that covers what type I and II errors are, how to Calculate an Alpha Level for one- and two-tailed tests, and why an Alpha Level of .05 commonly used. There is also a video included at the beginning of the video to explain the topics.
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  • Covers many topics within Hypothesis Testing, with a section dedicated to Significance level.
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  • Chapter excerpt from a book that covers the following topics: 1. Describe categories of statistical quality control (SQC). 2. Explain the use of descriptive statistics in measuring quality characteristics. 3. Identify and describe causes of variation. 4. Describe the use of control charts. 5. Identify the differences between x-bar, R-, p-, and c-charts. 6. Explain the meaning of process capability and the process capability index. 7. Explain the term Six Sigma. 8. Explain the process of acceptance sampling and describe the use of operating characteristic (OC) curves. 9. Describe the challenges inherent in measuring quality in service organizations.
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  • Chapter excerpt from a book that covers the following topics: 1. Describe categories of statistical quality control (SQC). 2. Explain the use of descriptive statistics in measuring quality characteristics. 3. Identify and describe causes of variation. 4. Describe the use of control charts. 5. Identify the differences between x-bar, R-, p-, and c-charts. 6. Explain the meaning of process capability and the process capability index. 7. Explain the term Six Sigma. 8. Explain the process of acceptance sampling and describe the use of operating characteristic (OC) curves. 9. Describe the challenges inherent in measuring quality in service organizations.
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  • Rresource covering what is meant by the term statistical quality control, why different types of control charts are necessary, how to construct and interpret a small variety of control charts, in particular those based on means and ranges, and how to describe in outline the relationship between hypothesis testing and statistical quality control.
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