Then we will compare this test statistic with a specified level of significance (alpha), just like we did with confidence intervals. This test statistic is a numerical quantity that measures the difference between the observed value and the expected value, divided by the standard error, which is the sample standard deviation. Next, we will calculate the desired test statistic from our random sample. The null hypothesis is the expected value of the population parameter, similar to the status quo, whereas the alternative hypothesis is a statement of negation of the null hypothesis as discussed by Penn State. Then we will write a declaration of our significance test, which will include a null hypothesis statement and an alternative hypothesis. Remember that a parameter always points to the population so that it will be either a population mean, population proportion, population slope, or some other population parameter. Hypothesis Testing Stepsįirst, we must identify the parameter of interest. Thus, we need a way to conclude an assumption is true or false by taking an appropriate sample and calculating a relevant statistic.Īnd knowing that we must expect that there will be some variation between the sample statistic that is calculated and the true population parameter, leads us to the understanding of statistical inferences (hypotheses). Now it would be unreasonable to assume that we can test the entire population to determine the feasibility of every claim one might have. Jenn, Founder Calcworkshop ®, 15+ Years Experience (Licensed & Certified Teacher) What Is Hypothesis Testing
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