1. Is there statistically significant evidence for the alternative hypothesis? 2

Question

1.  Is there statistically significant evidence for the alternative hypothesis?

2. Suppose you somehow find out that the actual proportion for the entire database population is 50%. Looking back at your test from question 1, was the result of your test a correct decision, a Type I error, or a Type II error. Explain.

3. Suppose you somehow find out that the actual proportion for the entire database population is 48 %. Looking back at your test from question 1, was the result of your test a correct decision, a Type I error, or a Type II error. Explain.

Explanation / Answer

1. If your p-value is less than or equal to the set significance level, the data is considered statistically significant. As a general rule, the significance level (or alpha) is commonly set to 0.05, meaning that the probability of observing the differences seen in your data by chance is just 5%.

Here pvalue<alpha=0.05 so test is statistically significant and we reject null hypothesis.

2. If population p=0.50 which means null hypothesis is true, but we have rejected it so we commit Type I error.

3.If population p=0.48, we made a correct decision of reject H0

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