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7: One-Sample Inference

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    Now that you have all this information about descriptive statistics and probabilities, it is time to start inferential statistics. There are two branches of inferential statistics: hypothesis testing and confidence intervals.

    Definition \(\PageIndex{1}\)

    Hypothesis Testing: making a decision about a parameter(s) based on a statistic(s).

    Definition \(\PageIndex{2}\)

    Confidence Interval: estimating a parameter(s) based on a statistic(s).

    • 7.1: Basics of Hypothesis Testing
      In hypothesis testing, you need to first have an understanding of what a hypothesis is, which is an educated guess about a parameter. Once you have the hypothesis, you collect data and use the data to make a determination to see if there is enough evidence to show that the hypothesis is true. However, in hypothesis testing you actually assume something else is true, and then you look at your data to see how likely it is to get an event that your data demonstrates with that assumption.
    • 7.2: One-Sample Proportion Test
    • 7.3: One-Sample Test for the Mean

    This page titled 7: One-Sample Inference is shared under a CC BY-SA 4.0 license and was authored, remixed, and/or curated by Kathryn Kozak via source content that was edited to the style and standards of the LibreTexts platform; a detailed edit history is available upon request.