Question:

How do I answer these questions in bold with more basic terms or more simplicity? As you can see below in italics, I have pulled together a very complex response but I want to show a response that's very basic and easy to understand. Can you help?

What is a hypothesis test? Why do we need to use them to make decisions about relating

sample results to the population; why can't we just make our decisions by the sample value?

Suppose an experiment or a survey is conducted and the related data has been given.

Generally, there will be circumstances which are abnormal and in most of the other situations,

the data will be in some rhythm or other.

But, there wouldn't be hectic volatility at the middle of the data items.

So, the given data items is known to be the null hypothesis.

If the null hypothesis is satisfying certain statistical tests, then we confirm and accept the

given hypothesis or null hypothesis is within the routine circumstances or simply within

certain significance level.

Otherwise, we say that the null hypothesis is not in the significant limits and so, we reject the

null hypothesis and choose an alternative hypothesis.

All results of statistical hypothesis tests are covered by two possibilities: Either the results are significant, or they aren't. The null hypothesis predicts a nonsignificant outcome. The alternate hypothesis predicts significance (Tanner & Youssef-Morgan, 2013). We need to use them to compare the difference in values between the population from the sample that it was drawn from, to the sample it was compared to. Especially within the industrial manufacturing spectrum. For example, the average pay scale for an electronic technician is 25 dollars an hour nationally. If you are being paid 23 dollars an hour, the probability is that your pay for your position is calculated by the overall averages of similar companies in that geographical region or by the change of cost of living, which is a fair wage of pay. There are a lot of other factors that can also contribute to that hypothesis.