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Chi-square test is a non-parametric test in hypothesis testing to know the association of two categorical features in bi-variate data or records. Non-parametric tests are distribution-free test…

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4 PART III: PROBABILITY AND THE FOUNDATIONS OF INFERENTIAL STATISTICS 8.2 FOUR STEPS TO HYPOTHESIS TESTING The goal of hypothesis testing is to determine the likelihood that a population parameter, such as the mean, is likely to be true. In this section, we describe the four steps of hypothesis testing that were briefly introduced in Section 8.1:

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Aug 11, 2020 · 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 in the sampling. A hypothesis test can help determine if a difference in the estimated proportions reflects a difference in the two population proportions.

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Resampling Statistics . Rationale Much of modern statistics is anchored in the use of statistics and hypothesis tests that only have desirable and well-known properties when computed from populations that are normally distributed.

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A second important point to remember is that confidence intervals and significance tests use sample statistics to estimate population parameters. If the data at hand constitute the entire population of interest, then constructing a confidence interval from these data is meaningless.

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The simplest way to compare two distributions is via the Z-test. The Z-test To compare two different distributions one makes use of a tenant of statistical theory which states that The error in the mean is calculated by dividing the dispersion by the square root of the number of data points. In the above diagram, there is some population mean that is the true intrinsic mean value for that population.