Significance Testing Principles

  • Presentation that covers: the significance of sample size, determination of sample size, factors that may affect sample size, and how to use sample size in a research or study.
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  • Presentation that applies the topics of power and sample size to examples in epigenetic epidemiology studies. Step by step solutions using statistical softwares G*Power and STATA are given.
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  • The process of sample size calculations, including relevant definitions, is explained and clear examples for different study designs are provided for illustration. A range of software packages and websites are discussed and evaluated
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  • Chapter from a textbook that covers the topic of sample size by giving a thorough background and then covering issues that are involved when determining the sample size.
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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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  • Resource that covers specific topics within significance testing, including significance levels. P-values and how to determine what qualifies as being statistically significant covered. Examples are given throughout the text to further explain the concepts.
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  • Video that explains what p-values and significance levels are in hypothesis testing.
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  • Video that will teach you how to interpret the P-Value and significance level for a two-tailed hypothesis test that is not rejected.
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  • Resource that covers what significance testing is and what it is used for. Describes the significance level and how it relates to the p-value with respect to hypothesis testing. A glossary of key concepts and terms is included at the end of the document.
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  • Short description of what the significance level is and what it takes for a result to be statistically significant.
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