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10: Hypothesis Testing with Two Samples

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    25682
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    • 10.1: Two Population Means with Unknown Standard Deviations
      This chapter deals with the following hypothesis tests: Independent groups (samples are independent) Test of two population means. Test of two population proportions. Matched or paired samples (samples are dependent) Test of the two population proportions by testing one population mean of differences.
    • 10.2: Comparing Two Independent Population Proportions
      Comparing two proportions, like comparing two means, is common. If two estimated proportions are different, it may be due to a difference in the populations or it may be due to chance. A hypothesis test can help determine if a difference in the estimated proportions reflects a difference in the population proportions.
    • 10.3.1: Matched or Paired Samples Part 1
      Comparing two proportions, like comparing two means, is common. If two estimated proportions are different, it may be due to a difference in the populations or it may be due to chance. A hypothesis test can help determine if a difference in the estimated proportions reflects a difference in the population proportions.
    • 10.3.2: Matched or Paired Samples Part 2
      When using a hypothesis test for matched or paired samples, the following characteristics should be present: Simple random sampling is used. Sample sizes are often small. Two measurements (samples) are drawn from the same pair of individuals or objects. Differences are calculated from the matched or paired samples. The differences form the sample that is used for the hypothesis test. Either the matched pairs have differences that come from a population that is normal or the number of difference
    • 10.4: Test of Two Variances
      Another of the uses of the FF distribution is testing two variances. It is often desirable to compare two variances rather than two averages.


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