The t-test is accurate for a hypothesis test when a simple random sample of size 19 from a population with a normal distribution is used, with a sample mean of 70 and sample standard deviation of 7. So, the suitable option is option (d).
In statistics, the process of hypothesis testing involves putting an analyst's presumption about a population parameter to the test. The methodology the analyst employs will depend on the type of data used and the goal of the study. To determine whether a claim is true, it is examined for plausibility using sample data. These data could originate from a broader population or a process that creates data. In the descriptions that follow, "population" will be used to refer to both of these situations.
An analyst performs hypothesis testing on a statistical sample with the intention of demonstrating the plausibility of the null hypothesis.
Statistical analysts measure and analyse a random sample of the population under study to test a hypothesis.All analysts use a random population sample to test the null hypothesis as well as the alternative hypothesis.
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