Hypothesis Testing Quiz | Online MCQs on Statistical Inference

1. In testing the statistical hypothesis, which of the following statement(s) is false?

For testing $H_0:\mu=\mu_0$, $H_1:\mu>\mu_0$, we reject $H_0$ for high values of the sample mean $\overline{X}$

The $p$-value measures the probability that the null hypothesis is true

The level of significance is the probability of type I error

In testing $H_0:\mu=\mu_0$, $H_1:\mu \ne \mu_0$, the critical region is two-sided.

The critical region is the values of the test statistic for which we reject the null hypothesis

2. Which of the following is NOT correct?

The $p$-value measures the probability that the null hypothesis is true

The probability of a type I error is controlled by the selection of the level of significance $\alpha$

The probability of a type II error is controlled by the sample size $(n)$

The power of a test depends upon the sample size and the distance between the null hypothesis and the alternative hypothesis

The rejection region is controlled by the $\alpha$ and the alternative hypothesis

3. In statistical testing of the hypothesis, what happens to the region of rejection when the level of significance $\alpha$ is reduced?

The answer depends on the value of $\beta$

The rejection region is reduced in size

The rejection region is unaltered

The rejection region is increased in size

The answer depends on the form of the alternative hypothesis

4. In testing the statistical hypothesis, which of the following statement(s) is false?

In testing $H_0:\mu=\mu_0$, $H_1:\mu \ne \mu_0$, the critical region is two-sided.

For testing $H_0:\mu=\mu_0$, $H_1:\mu>\mu_0$, we reject $H_0$ for high values of the sample mean $\overline{X}$

The $p$-value measures the probability that the null hypothesis is true

The level of significance is the probability of type I error

The critical region is the values of the test statistic for which we reject the null hypothesis

5. Which of the following statements is correct

The p-value measures the probability of making a Type II error

A large p-value indicates that the data is consistent with the alternative hypothesis

The p-value measures the probability that the hypothesis is true

An extremely small p-value indicates that the actual data differs significantly from the expected if the null hypothesis is true

The larger the

Hypothesis Testing Quiz 3