Question

If the P-value is 0.02, it means that the probability of obtaining the sample statistic is 2%, if the null hypothesis is true. the probability of obtaining the sample statistic is 2%. the probability of obtaining the sample statistic is 2%, if the alternate hypothesis is true. the probability that the null hypothesis is true, is 2%.

Answer 1

Answer:

Option a) The probability of obtaining the sample statistic is 2%, if the null hypothesis is true.

Step-by-step explanation:

We are given that the p-value is 0.02

Converting it into percentage:

$0.02\times 100 = 2\%$

P-value can be explained as:

• P-value can be described as probability of the occurrence of a given event

• The p-value, or probability, is the probability of finding the observed results when the null hypothesis $H_0$ of a study is true.
• If the p-value is less than the chosen significance level then we reject the null hypothesis and accept that the sample gives reasonable evidence to support the alternative hypothesis.
• A smaller p-value means that there is stronger evidence in favor of the alternative hypothesis.
• The p-value is the probability to the right of our test statistic.
• The smaller is the p-value, the stronger are the evidence against the null hypothesis and in favor of alternative hypothesis.

Hence, Option a) correctly describes the p-values as:

The probability of obtaining the sample statistic is 2%, if the null hypothesis is true.