Hypothesis testing in Statistics
Learn Hypothesis Testing in Statistics. This is taught in Applied Mathematics and Statistics.
You are introduced to the null hypothesis. When you make an assumption about a population parameter, you get a null hypothesis. We define another hypothesis which is the opposite of this, called the Alternate hypothesis.
You'll learn the hypothesis test for population mean which involves one tailed test and two tailed test. In this context, you learn about upper and lower one tailed test. If the null hypothesis is true and if we reject it , we get a Type I error.
If the alternate hypothesis is true and we reject it, we get a Type II error. The level of significance is the probability of making a Type I error. You'll also learn how to evaluate the test statistic.
You'll also learn how to calulate the rejection rule, using the p value and the critical value approach. Next , you move on to interval estimation for a two tailed hypothesis.
Learn how to calculate the confidence intervals and to use it in hypothesis testing. To learn more, watch this video.
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