Week 5: Hypothesis Testing - Decision Tool 5 5 unread replies. 9 9 replies. In y

Question

Week 5: Hypothesis Testing - Decision Tool

5 5 unread replies. 9 9 replies.

In your environment (business or personal), please describe a hypothesis test related to a decision. What would be your data? What would be your null hypothesis? What would be your alternate hypothesis? What would be your Type 1 and Type 2 errors relative to your decision? Suppose you have a p-value of 0.01, what does this mean relative to your problem and decision? Suppose the p-value is 0.20, what does this mean relative to your problem and decision?

Explanation / Answer

Solution:

I might want to know what is the average monthly sale of the product produced by my business. Suppose I presume that the average monthly sales is 100 units. So I might want to check (by taking sample), whether my claim is correct or whether the observed average monthly sales are statistically different from 100.

So the null hypothesis here: H0: average monthly sales = 100

And alternative hypothesis: HA: average monthly sales do not equal 100

Type I error: when we reject a true null hypothesis, we commit type 1 error

Type IIerror: when we accept a false null hypothesis, we commit type 2 error

The p-values denote the minimum “level of significance” at which we reject the null hypothesis. The p-value of 0.01 means the null hypothesis (that average monthly sales are 100) would be rejected at any level of significance more than 1% i.e. at level of significance more than 1%,average monthly sales are statistically significant from 100.

The p-value of 0.2 denotes that null hypothesis is accepted at all standard level of significance (1%, 5%, or 10%) which means that average monthly sales are not statistically significant from 100.

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