Type 1 and 2 Errors

Define a Type I error?

• The failure to reject a false null hypothesis
• Rejecting a true null hypothesis
• The acceptance to reject a null hypothesis
• Accepting a true null  hypothesis

State the null and alternative hypotheses:

"The average weight of dogs is 15.6 pounds."

• Ho: μ = 15.6 and H1: μ ≠ 15.6

• Ho: μ = 15.6 and H1: μ > 15.6

• Ho: μ = 15.6 and H1: μ < 15.6

What is the definition of a hypothesis?

• A claim on a particular parameter of a population.

• It evaluates if a population parameter is equal to the stated sample statistics.

• Determination of the level of significance and the sample size.

• A statement on statistical decision.

• A statement on managerial conclusion.

• She concludes the town's unemployment rate is not 9% when it actually is.

• She concludes the town's unemployment rate is not 9% when it actually is not.
  

• She concludes the town's unemployment rate is 9% when it actually is.
  

• She concludes the town's unemployment rate is 9% when it actually is not.
  

Which of the following best describes a type II error?

• The null is true, but we mistakenly reject it.

• The null is false and we reject it.

• The null is false, but we fail to reject it.

• The null is true but we fail to reject it.

• Te null is false, and we reject it.

Which of the following is the FIRST step of a hypothesis test?

• Check assumptions & conditions
• Find your test statistic
• State your conclusion
• State your null & alternative hypotheses

Bottles of water have a label stating that the volume is 12 oz. A consumer group suspects the bottles are under‐filled and plans to conduct a test. A Type I error in this situation would mean

• the consumer group concludes the bottles have less than 12 oz. when the mean actually is 12 oz.

• the consumer group does not conclude the bottles have less than 12 oz. when the mean actually is less than 12 oz.

• the consumer group has evidence that the label is incorrect.

What does a Type 1 error signify in statistical hypothesis testing?

• Rejecting a true null hypothesis

• Failing to reject a false null hypothesis

• Accepting a true null hypothesis

• None of the above

What is the probability of making a Type 1 error known as?

• Delta (δ)

• Alpha (α)

• Gamma (γ)

• Beta (β)

What does the probability of making a Type 2 error represent?

• The power of the test

• The significance level of the test

• Beta (β)

• Alpha (α)