4. Explain the meaning of a level of significance of 5%. Why is a level of
significance needed for every hypothesis test?

5% significance level indicates the level of risk, error or exactness. It guides our conclusion on which hypothesis a data supports

Level of significance defined as the possibility, probability or chances of rejecting a null hypothesis when it's results is valid.

For every statistical hypothesis, the result has propency or likeliness to be exact or not. That is, it has chances of containing a type of error referred to as level of significance.

Now, a 5% significance level implies that, the statistical results or analysis has 95% reliability or confidence level.

In other words, a 5% significance level indicates that a result has 0.05 RISK level.

The level of significance is needed for every hypothetical test because it indicates validity of each hypothesis data. It gives confidence such that one is at peace to know the hypothesis a particular data supports

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