Statistical hypothesis and hypothesis testing

Statistical hypothesis is the statistical term that may be accepted or rejected. Any hypothesis may be true or false. Just for example, your fraind state that today will be rain. Claim of your friend is called a hypothesis. This hypothesis may be true or not. To make a decision that today will be rain, there need a hypothesis testing. Hypothesis test will provide you thr clear idea to take a decidion about the rain will be or not? The ice cream manufacture company will boost their sales in next winter. Let it is a hypothesis. This hypothesis may be true or false. Hypothesis testing is a probability that determines that the given statement is true or false. Hypothesis testing are done by following steps, First step of testing of hypothesis is introducing null hypothesis and alternative hypothesis Test statistics is the second step of hypothesis testing. P-value is the third step of hypothesis testing in order to accepting or rejecting the hypothesis. Compareing the p-value with significance The two pair of statement of a population parameter is true and false. If one is null hypothesis then another will be alternative hypothesis. If the hypothesis testing gives a decision that null hypothesis should reject then it clearly prove that alternative hypothesis should be accept.