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13.1: Introduction

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    140490

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    Have you ever wondered if lottery winning numbers were evenly distributed or if some numbers occurred with a greater frequency? What about if sports injuries were evenly distributed across different months of the season or if some injuries occurred with a greater frequency? How about if the types of physical activities people preferred were different across different age groups? What about if a ventilated metabolic cart was measuring approximately the same amount of oxygen consumption during repeated baseline tests? You could answer these questions by conducting a hypothesis test.

    You will now study a new distribution, one that is used to determine the answers to such questions. This distribution is called the chi-square distribution.

    In this chapter, you will learn the three major applications of the chi-square distribution:

    1. the goodness-of-fit test, which determines if data fit a particular distribution, such as in the sports injury example
    2. the test of independence, which determines if events are independent, such as in the physical activity example
    3. the test of a single variance, which tests variability, such as in the metabolic cart example

    This page titled 13.1: Introduction is shared under a CC BY-NC 4.0 license and was authored, remixed, and/or curated by OpenStax via source content that was edited to the style and standards of the LibreTexts platform.