Hypothesis Testing

  1. Null Hypothesis: Previous value and observed values from the claim are same.
  1. Chi-squared Test : A chi-square test requires categorical variables, usually only two, but each may have any number of levels.
  2. t-student Test : A t-test requires two variables; one must be categorical and have exactly two levels, and the other must be quantitative and be estimable by a mean. For example, the two groups could be Republicans and Democrats, and the quantitative variable could be age.
  3. Fisher’s Z Test: In a z-test, the sample is assumed to be normally distributed.
  4. ANOVA Test: It is also called an analysis of variance and is used to compare multiple (three or more) samples with a single test. It is used when the categorical feature has more than two categories.

References:

https://www.statisticshowto.com/probability-and-statistics/hypothesis-testing/

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