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  • Kimberley Polly defines test statistics and p-values, explaining their roles in hypothesis testing using tail probabilities. The discussion covers distinguishing between truthful information and lies to understand Type 1 and Type 2 errors.
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Kimberley Polly explains the concepts of Type I and Type II errors within the context of statistical hypothesis testing. The lesson demonstrates how to define these errors using qualitative data regarding the death rates of prisoners to illustrate the risks associated with incorrect inferential conclusions. Kimberley Polly demonstrates how to conduct a chi-square goodness-of-fit test using statistical software. By analyzing frequency data from 500 die rolls, the process covers inputting observed frequencies, determining expected values for a fair die, verifying assumptions, and calculating test statistics to evaluate the consistency of the results. Section0701Video5 Section0701Video3

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