Consider the following statement and identify the wrong statements. Statement I: Accepting null hypothesis, when it is false, is called a level of significance. Statement II: $$1 – \alpha $$ is called power of a test. Statement III: Critical value of $$Z$$ – static for two-tailed test at 5% level of significance is 1.96.

The correct answer is: Statements I and II.

Statement I is incorrect because accepting the null hypothesis when it is false is called a type II error. Statement II is correct because $1 – \alpha$ is called the power of a test. Statement III is correct because the critical value of $Z$-statistic for a two-tailed test at 5% level of significance is 1.96.

Here is a brief explanation of each statement:

• Statement I: Accepting null hypothesis, when it is false, is called a level of significance.

This is incorrect. Accepting the null hypothesis when it is false is called a type II error. The level of significance is the probability of rejecting the null hypothesis when it is true.

• Statement II: $1 – \alpha$ is called power of a test.

This is correct. The power of a test is the probability of rejecting the null hypothesis when it is false. It is equal to $1 – \alpha$, where $\alpha$ is the level of significance.

• Statement III: Critical value of $Z$-static for two-tailed test at 5% level of significance is 1.96.

This is correct. The critical value of $Z$-statistic for a two-tailed test at 5% level of significance is 1.96. This means that if the $Z$-statistic is greater than or equal to 1.96, we reject the null hypothesis.