11.0: Introduction to the Chi-Square Distribution

Business Statistics · LibreTexts

0%

Contents

    Text

    Size
    100%
    Theme
    Typeface
    Line length
    Spacing

    From LibreTexts, under CC BY 4.0, as the source states it; its equations are written in TeX, which the PDF shows typeset. This page at LibreTexts.

    Have you ever wondered if lottery winning numbers were evenly distributed or if some numbers occurred with a greater frequency? How about if the types of movies people preferred were different across different age groups? What about if a coffee machine was dispensing approximately the same amount of coffee each time? You could answer these questions by conducting a hypothesis test.

    This is a photo of a pile of grocery store receipts. The items and prices are blurred.
    Figure \(\PageIndex{1}\): The chi-square distribution can be used to find relationships between two things, like grocery prices at different stores. (credit: Pete/flickr)

    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 lottery example
    2. the test of independence, which determines if events are independent, such as in the movie example
    3. the test of a single variance, which tests variability, such as in the coffee example

    This page titled 11.0: Introduction to the Chi-Square Distribution was last modified on Thu, 29 Jul 2021 03:08:13 GMT and is shared under a CC BY 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.