16: Hypothesis Testing

Statistical Thinking for the 21st Century · LibreTexts

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    Learning Objectives

    • Identify the components of a hypothesis test, including the parameter of interest, the null and alternative hypotheses, and the test statistic.
    • Describe the proper interpretations of a p-value as well as common misinterpretations
    • Distinguish between the two types of error in hypothesis testing, and the factors that determine them.
    • Describe how resampling can be used to compute a p-value.
    • Define the concept of statistical power, and compute statistical power for a given statistical test.
    • Describe the main criticisms of null hypothesis statistical testing

    In the first chapter we discussed the three major goals of statistics:

    • Describe
    • Decide
    • Predict

    In this chapter we will introduce the ideas behind the use of statistics to make decisions – in particular, decisions about whether a particular hypothesis is supported by the data.

    This page titled 16: Hypothesis Testing was last modified on Sun, 24 Apr 2022 05:51:03 GMT and is shared under a CC BY-NC 4.0 license and was authored, remixed, and/or curated by Russell A. Poldrack via source content that was edited to the style and standards of the LibreTexts platform.