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Mathematics LibreTexts

10: Statistics

  • Page ID
    34239
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    • 10.1: Introduction
    • 10.2: Populations and Samples
      Before we begin gathering and analyzing data we need to characterize the population we are studying.
    • 10.3: Categorizing data
      Once we have gathered data, we might wish to classify it. Roughly speaking, data can be classified as categorical data or quantitative data.
    • 10.4: Sampling methods
    • 10.5: How to mess things up before you start
      There are number of ways that a study can be ruined before you even start collecting data. The first we have already explored – sampling or selection bias, which is when the sample is not representative of the population. One example of this is voluntary response bias, which is bias introduced by only collecting data from those who volunteer to participate. This is not the only potential source of bias.
    • 10.6: Experiments
      So far, we have primarily discussed observational studies – studies in which conclusions would be drawn from observations of a sample or the population. In contrast, it is common to use experiments when exploring how subjects react to an outside influence. In an experiment, some kind of treatment is applied to the subjects and the results are measured and recorded.
    • 10.7: Exercise

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