GAS B ASSESSMENT

What is the null hypothesis (H₀) in hypothesis testing for a population proportion?

• The population proportion is different from a given value.

• The population proportion is equal to a given value.

• The population proportion is greater than a given value.

• The population proportion is less than a given value.

In a hypothesis test, what does the alternative hypothesis (H₁) represent?

• The assumption that the population proportion remains the same.

• The assumption that there is no significant difference.

• The claim that the population proportion has changed.

• The assumption that the sample size is too small.

If the level of significance (α) is 0.05, what does this mean?

• There is a 5% chance of correctly rejecting the null hypothesis.

• There is a 5% chance of incorrectly rejecting the null hypothesis.

• The probability of making a correct decision is 5%.

• The probability of accepting the null hypothesis is 5%.

A school claims that 70% of its students participate in extracurricular activities. A survey of 150 students found that 105 participated. What is the sample proportion (p̂)?

• 0.50

• 0.60

• 0.70

• 0.80

The rejection region is determined by:

• The critical value based on the level of significance.

• The sample size alone.

• The calculated p-value.

• The mean and standard deviation of the sample

If the computed test statistic falls in the rejection region, what should be done?

• Accept the null hypothesis.

• Reject the null hypothesis.

• Increase the sample size and repeat the test.

• Change the level of significance.

A hypothesis test was conducted at a 5% significance level, and the computed p-value was 0.03. What should be the conclusion?

• Reject the null hypothesis.

• Fail to reject the null hypothesis.

• Increase the sample size.

• Conduct a different test.

What does it mean when the null hypothesis is not rejected?

• The sample proportion is exactly the same as the population proportion.

• The test was conducted incorrectly.

• The null hypothesis is proven to be true.

• There is not enough evidence to support the alternative hypothesis.