Hypothesis Testing Quiz

Which type of error can a hypothesis test help identify?

• Typographical errors

• Systematic error

• Personal bias

• Calculation mistakes

What is the purpose of a hypothesis test?

• To confirm all observed differences are significant

• To measure the probability that differences are due to random error

• To ensure all data is accurate

• To eliminate all random errors

What is the first step in hypothesis testing?

• Calculate value of a parameter (e.g., t)

• Compare calculated value to critical value

• Determine the sample size

• Identify the null hypothesis

What does it mean if the critical value is greater than the calculated value?

• It is random error at that probability

• The hypothesis is accepted

• The sample size is too small

• The test is invalid

What is the null hypothesis (H₀) in hypothesis testing?

• That everything is random error

• That the sample size is adequate

• That the test is one-tailed

• That the critical value is accurate

What is a Type 1 error in hypothesis testing?

• False positive

• False negative

• True positive

• True negative

What happens if you reject a difference that is real in hypothesis testing?

• Type 2 error

• Type 1 error

• No error

• True positive

How can you reduce the chance of a Type 1 error?

• Assess at a higher probability, e.g., 99%

• Use a smaller sample size

• Ignore the error

• Repeat the test multiple times

What is the risk of repeating hypothesis tests?

• Increased chance of error

• Decreased chance of error

• No change in error probability

• Guaranteed correct results

Which of the following is a use of the t-test?

• Comparing measured data to a single value

• Testing for independence in categorical data

• Analyzing variance between groups

• Estimating population parameters