Statistical Hypothesis Test
Statistical Hypothesis Test is a method of making decisions using data from a scientific study. It is a process of testing whether a hypothesis about a population parameter is supported by the evidence provided by a sample of data. The test involves formulating a null hypothesis and an alternative hypothesis, selecting a significance level, calculating a test statistic, and determining the probability of obtaining the observed results or more extreme results if the null hypothesis is true. If the probability is less than the significance level, the null hypothesis is rejected in favor of the alternative hypothesis. Statistical hypothesis testing is widely used in data science and artificial intelligence to make decisions based on data and to evaluate the performance of machine learning models.
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