Null Hypothesis states that the value of a population parameter ($\mu, \sigma$) is equal to claimed value. Test Null Hypothesis** assumes it is true and test to reject or fail to reject $H_0$.
Alternative hypothesis: $H_1$ or $H_A$ is the statement that the parameter has a value that differs from that of the null hypothesis.
If we conduct a study and want to use a hypothesis test to support our claim, the claim must be worded so that it because the alternative hypothesis.
Select the significance level $\alpha$ based on the seriousness of a type I error. Make $\alpha$ small is the consequneces of rejecting a true $H_0$ are severe. $\alpha=0.05$ and $\alpha=0.01$ are very common.
$\alpha$ is the probability that the test statistical will fall in the critical region whne the null $H_0$ is true.
The test statistic is a value used in making a decision about the null hypothesis, and is found by converting the sample statistic to score with the assumption that the null hypothesis is true.