Hypothesis Testing Skills

What is the first step in hypothesis testing?

• State the null and alternative hypotheses

• Analyze the results

• Choose the significance level

• Collect data

Define the null hypothesis in the context of hypothesis testing.

• A statement that there is a significant difference or effect

• A hypothesis that is never tested

• A statement that is always proven to be true

• A statement that there is no significant difference or effect.

Explain the concept of Type I error in hypothesis testing.

• When the p-value is greater than the significance level.

• When the null hypothesis is accepted when it is actually false.

• When the null hypothesis is rejected when it is actually true.

• When the alternative hypothesis is rejected when it is actually true.

How do you determine the appropriate test statistic for a hypothesis test?

• Choose the first test statistic that comes to mind

• Flip a coin

• Consider the type of data and the specific hypothesis being tested

• Ask a friend for their opinion

What is the significance level in hypothesis testing and how is it determined?

• The significance level is the probability of accepting the null hypothesis when it is actually true, and it is determined after conducting the test.

• The significance level is the probability of accepting the null hypothesis when it is actually false, and it is determined before conducting the test.

• The significance level is the probability of rejecting the null hypothesis when it is actually true, and it is determined before conducting the test.

• The significance level is the probability of rejecting the alternative hypothesis when it is actually true, and it is determined after conducting the test.

What is the alternative hypothesis and how is it formulated?

• The alternative hypothesis is always the same as the null hypothesis

• The alternative hypothesis is formulated based on the research question and represents the possibility of a significant effect or relationship in the population.

• The alternative hypothesis is based on personal beliefs and opinions

• The alternative hypothesis is not necessary in hypothesis testing

Describe the process of interpreting the results of a hypothesis test.

• Ask a colleague for their opinion

• Calculate the mean and standard deviation of the sample

• Flip a coin to make the decision

• Compare the p-value to the significance level, make a decision about the null hypothesis, and draw conclusions based on the results.

What is the role of Type II error in hypothesis testing?

• It is the probability of failing to reject a false null hypothesis.

• It is the chance of correctly rejecting a false null hypothesis.

• It is the likelihood of accepting a false null hypothesis.

• It is the probability of rejecting a true null hypothesis.

Explain the difference between Type I and Type II errors.

• Type I error occurs when the null hypothesis is not rejected when it is actually false

• Type II error occurs when the null hypothesis is rejected when it is actually true

• Type I error occurs when the null hypothesis is accepted when it is actually false

• Type I error occurs when the null hypothesis is rejected when it is actually true, while Type II error occurs when the null hypothesis is not rejected when it is actually false.

How do you select the critical value for a hypothesis test?

• Based on the significance level and degrees of freedom

• Using a Magic 8-Ball

• By flipping a coin

• Based on the weather forecast