In Q&A format answer the following

1. In 200-300-words: Suppose that you perform a significance test regarding a population mean and that the evidence does not warrant rejection of the null hypothesis. When formulating the conclusion to the test, why is the phrase fail to reject the null hypothesis more accurate than the phrase accept the null hypothesis? Why can the null hypothesis not be proved? Explain. 2. Write a response in 100 words for the following: When a significance test regarding a population mean does not justify the rejection of the null hypothesis, this means that the conclusion would be more accurate stating that the evidence failed to reject the null hypothesis. In other words, the entire purpose of the test was to find evidence why the null hypothesis cannot be proved. If it cannot do this, it failed. In this sense, it is the only real way to explain this question. In hypothesis testing the null hypothesis is never proved or established, but is possibly disproved, in the course of the test. Every experiment may be said to exist only in order to give the facts a chance of disproving the null hypothesis. In other words, hypothesis testing begins with the statement that the “null” is true and it is up to the experimenter/researcher to prove it false. If the researcher proves it to be false, then the “null” is rejected. But if the researcher cannot prove that the “null” is false, it does not mean the “null” will be accepted as true because we had initially set out with the assumption that the “null” is true. This is why we either reject the null hypothesis or fail to reject the null hypothesis, but never accept it. 3. Respond to the following in minimum 60 words: The purpose of a significance test is generally to decide whether or not a given hypothesis is likely or unlikely to occur with given data. Hypothesis testing gives us results for situations that are testable. When formulating the conclusion to the test, the phrase fail to reject the null hypothesis is more accurate than the phrase accept the null hypothesis because when saying fail to reject the null hypothesis, it not implying that the null hypothesis is actually true. Rather the phrase fail to reject the null hypothesis is just stating that there isn't enough supporting evidence to reject. When using the phrase accept the null hypothesis, it is not as accurate because it means that one can only find evidence against it. The null hypothesis can not be proven because it can only be proven to be false; reason for this justification is because the science and hypothesis testing are set on the foundation of the logic of falsification. The null can only be rejected or fail to reject. When conducting the hypothesis testing, the null hypothesis is the complete opposite of the alternate hypothesis. and the testers or researchers are working toward rejecting or nullifying the null hypothesis, thus an alternative hypothesis is formulated. Black, K. (2017). Business Statistics for Contemporary Decision making (9th Ed). Hoboken, NJ: John Wiley & Sons, Inc. 4.In 200-300 words: Distinguish between a Z test and a t-test. Provide an example of each one that might be appropriate for a place you’ve been employed at or work that you’ve done. 5. In 150-200 words summarize the above.