PrepGo

AP Statistics Practice Quiz: Setting Up a Test for the Slope of a Regression Model

Written by AP Content Team, Verified for 2026 AP Exams, Last updated: May 2026

Test your understanding with short quizzes. This quiz has 16 questions to check your progress.

Question 1 of 16

Which statistical procedure is the appropriate method for testing a claim about the slope of a population regression model?

All Questions (16)

Which statistical procedure is the appropriate method for testing a claim about the slope of a population regression model?

A) A t-test for a slope

B) A chi-square test for independence

C) A two-sample z-test for means

D) A one-sample t-test for a mean

Correct Answer: A

The provided content explicitly states that 'The appropriate test for the slope of a regression model is a t-test for a slope.'

A researcher wants to determine if there is a statistically significant linear relationship between the number of hours a student studies and their score on an exam. Which is the most appropriate testing method to select?

A) A test for the y-intercept of the regression model

B) A t-test for the slope of the regression model

C) A chi-square test of association

D) A two-sample t-test for the difference in mean scores

Correct Answer: B

To determine if a significant linear relationship exists, one must test the slope of the regression model. The content identifies the appropriate method for this as a t-test for a slope.

In a significance test for the slope of a regression model, what is the general form of the null hypothesis?

A) H0: β = β₀

B) H0: b = b₀

C) H0: μ₁ = μ₂

D) H0: p = p₀

Correct Answer: A

The content states, 'The null hypothesis for a t-test for a slope is H0: beta = beta0'. The Greek letter beta (β) represents the population slope, while β₀ is the hypothesized value.

A statistician is testing whether there is any linear relationship between two quantitative variables. What is the most common null hypothesis for this test?

A) H0: β = 1

B) H0: β > 0

C) H0: β = 0

D) H0: β ≠ 0

Correct Answer: C

To test for the existence of any linear relationship, the null hypothesis posits that the population slope (β) is zero, which indicates no linear relationship. The general form is H0: β = β₀, and in this common case, the hypothesized value β₀ is 0.

A researcher hypothesizes that as the amount of fertilizer increases, crop yield will also increase. Which of the following is an appropriate alternative hypothesis for a test of the slope of the regression model?

A) Ha: β = 0

B) Ha: β < 0

C) Ha: β ≠ 0

D) Ha: β > 0

Correct Answer: D

The researcher expects a positive relationship (as one variable increases, the other increases). This translates to a population slope (β) that is greater than zero. Therefore, the appropriate one-sided alternative hypothesis is Ha: β > 0.

When testing for any significant linear association between two variables, without a prior belief about the direction of the relationship, what is the appropriate alternative hypothesis?

A) Ha: β ≠ 0

B) Ha: β > 0

C) Ha: β = 0

D) Ha: β < 0

Correct Answer: A

A two-sided alternative hypothesis is used when the researcher is interested in detecting a relationship in either a positive or negative direction. This is represented by Ha: β ≠ 0.

An economist wants to test the claim that there is a negative linear relationship between a country's unemployment rate and its GDP growth rate. Which set of hypotheses is appropriate for this test?

A) H0: β = 0 vs. Ha: β > 0

B) H0: β = 0 vs. Ha: β ≠ 0

C) H0: β = 0 vs. Ha: β < 0

D) H0: β < 0 vs. Ha: β = 0

Correct Answer: C

The null hypothesis should assume no linear relationship (β = 0). The economist's claim is for a negative relationship, which means the population slope would be less than zero. Therefore, the appropriate alternative hypothesis is Ha: β < 0.

Which of the following is a required condition for conducting a significance test for the slope of a regression model?

A) The sample size must be greater than 30.

B) The data must come from a randomized experiment.

C) The standard deviation of the response variable y is constant for all values of the explanatory variable x.

D) The explanatory variable x must be normally distributed.

Correct Answer: C

Based on the provided content, one of the four required conditions to check is that the 'standard deviation of y is constant'. The other options are not required conditions for this specific test.

All of the following are conditions that must be verified before performing a t-test for the slope of a regression model EXCEPT:

A) The relationship between the variables is linear.

B) The observations are independent.

C) The sample of the explanatory variable x is selected randomly from a normal population.

D) For each value of x, the corresponding responses of y are normally distributed.

Correct Answer: C

The required conditions are that the relationship is linear, data are independent, the standard deviation of y is constant, and responses are normal for each x. There is no requirement that the explanatory variable x be normally distributed.

When verifying the conditions for a t-test for a slope, what is the purpose of checking the 'Linear' condition?

A) To ensure that the standard deviation of y is the same for all x-values.

B) To ensure that a straight line is an appropriate model for the relationship between the variables.

C) To ensure that individual data points do not influence each other.

D) To ensure that the response variable follows a t-distribution.

Correct Answer: B

The 'Linear' condition requires checking that the underlying relationship between the explanatory variable (x) and the response variable (y) is, in fact, linear, making a straight line an appropriate model.

The 'Independence' condition for a regression slope test requires that:

A) The explanatory and response variables are not correlated.

B) The individual observations are independent of one another.

C) The residuals are normally distributed.

D) The slope and the y-intercept of the regression line are independent.

Correct Answer: B

The independence condition refers to the individual observations in the dataset. It means that knowing the outcome of one observation should not provide information about the outcome of another.

What does the 'Normal' condition for a significance test for the slope of a regression model state?

A) The distribution of the explanatory variable (x) must be approximately normal.

B) The overall distribution of the response variable (y) must be approximately normal.

C) For any given value of x, the corresponding y-values are normally distributed.

D) The sample size must be large enough for the Central Limit Theorem to apply.

Correct Answer: C

The 'Normal' condition specifically requires that 'responses are normal for each x.' This means that for any fixed value of the explanatory variable, the distribution of the possible responses for y follows a normal distribution.

In the context of verifying conditions for a regression slope test, what does it mean for the 'standard deviation of y to be constant'?

A) The variability of the explanatory variable x is the same across its range.

B) The variability of the response variable y is the same for all values of x.

C) The sample standard deviation of y is equal to the population standard deviation of y.

D) The data points all lie exactly on the regression line.

Correct Answer: B

This condition means that the spread (measured by standard deviation) of the y-values around the true regression line is the same regardless of the x-value. The content states this as 'standard deviation of y is constant'.

A student is preparing to conduct a t-test for the slope of a regression model. They have already confirmed that the relationship is linear and that the observations are independent. What other conditions must be verified?

A) The sample size is large and the x-values are normally distributed.

B) The standard deviation of y is constant for each x, and the responses of y are normal for each x.

C) The data was collected from a simple random sample and the population is at least 10 times the sample size.

D) The correlation coefficient is strong and the residuals sum to zero.

Correct Answer: B

The four conditions are: Linear, Independent, Normal, and Equal Standard Deviation. The student has checked the first two, so they must still check that the 'standard deviation of y is constant' and that 'responses are normal for each x'.

Which of the following pairs correctly identifies a possible null hypothesis and a required condition for a t-test for the slope of a regression model?

A) Hypothesis: H0: b = 0; Condition: The distribution of x-values is normal.

B) Hypothesis: H0: β = 0; Condition: The relationship between the variables is linear.

C) Hypothesis: H0: β ≠ 0; Condition: The observations are dependent.

D) Hypothesis: H0: b = β; Condition: The standard deviation of x is constant.

Correct Answer: B

A valid null hypothesis tests the population slope (β), commonly H0: β = 0. A required condition is that the relationship between the variables is linear. Option B correctly lists both. Option A uses the sample slope (b). Option C has an invalid null hypothesis form and an incorrect condition. Option D has an invalid hypothesis and an incorrect condition.

A researcher collects data on the age and selling price of used cars. They plan to perform a t-test for the slope of the regression line. Which of the following describes a necessary check of the conditions?

A) Check if the ages of the cars are normally distributed.

B) Check if the overall distribution of selling prices is normally distributed.

C) Check if the selling prices for cars of a specific age (e.g., 5-year-old cars) are normally distributed.

D) Check if the sample of cars was selected using an independent random sampling method.

Correct Answer: C

The 'Normal' condition states that 'responses are normal for each x'. In this context, x is the age and y is the selling price. Therefore, the condition requires checking if the selling prices (y) for a specific age (x) are normally distributed. It does not require the overall distribution of x or y to be normal.