AP Statistics

Which of the following best describes a Type I 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.

• The null is true, and we fail to reject it.

To test a claim about a mean, when the population standard deviation is unknown we use:

• z procedures
• Pythagorean Theorem
• t procedures
• np > 10 and n(1-p) > 10

Tags

CCSS.HSS.IC.B.4

CCSS.HSS.IC.A.1

The null hypothesis is represented by:

• Ha

• Ho

• t*

• HP

• μ

The null hypothesis always contains a(an):

• < or >

• =

• >

• = or >

• ≠

Tags

CCSS.HSS.IC.A.1

CCSS.HSS.IC.B.5

When p-value is greater than alpha we:

• Accept Ho
• Accept Ha
• Fail to reject Ho
• Reject Ho

Margin of error equals:

• Critical Value ∗ standard Error
• z*
• 1.96
• Standard Error

Tags

CCSS.HSS.IC.B.4

What is the Power of a test?

• A strong force
• The probability that we correctly reject a false null.
• The probability that we correctly accept a true null.
• How tough it is.

Tags

CCSS.HSS.MD.B.7

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.

What does it mean when a test is statistically significant?

• it has reached alpha level status
• the test statistic had a P-value higher than the alpha level
• the test statistic had a P-value lower than the alpha level
• it is important in practical terms

Tags

CCSS.HSS.IC.B.5

How can you reduce both Type I and Type II errors?

• it can't be reduced
• redo the tests
• increase the sample size
• tamper with the data

Tags

CCSS.HSS.IC.B.5

CCSS.HSS.MD.B.7