Question 1

Which scatterplot below depicts a stronger linear relationship? Why?

Accepted Answer

A) Scatterplot (i) shows a stronger linear relationship because it has less vertical variation between points. 
B) Scatterplot (i) shows a stronger linear relationship because it has more vertical variation between points. 
C) Scatterplot (ii) shows a stronger linear relationship because it has less vertical variation between points. 
D) Scatterplot (ii) shows a stronger linear relationship because it has more vertical variation between points. 
A) Scatterplot (i) shows a stronger linear relationship because it has less vertical variation between points. 
B) Scatterplot (i) shows a stronger linear relationship because it has more vertical variation between points. 
C) Scatterplot (ii) shows a stronger linear relationship because it has less vertical variation between points. 
D) Scatterplot (ii) shows a stronger linear relationship because it has more vertical variation between points.

Question 2

Which scatterplot below depicts a stronger linear relationship? Why? Explain what the scatterplot shows regarding a tree's volume.

Accepted Answer

Scatterplot (ii) shows a stron

Question 3

Use the following information for following questions .
Suppose data were recorded for 100 employees of a large company that included annual salaries
and the number of years the employee has been in their current position. The mean annual salary
was $58,000 with a standard deviation of 12,500. The mean number of years in the current
position is 10 with a standard deviation of 3. The correlation coefﬁcient between the two
variables is approximately 0.93.
-Determine the correct value of the slope for the linear model that predicts annual salary from the number of years in current position and interpret it in context.

Accepted Answer

@#IMG-DLM& So, the slope is $3875. For e

Question 4

Suppose temperatures and monthly ice cream sales were measured for 100 randomly selected cities. Which variable is the explanatory variable and which one is the response?

Accepted Answer

A) Temperature is the explanatory variable and ice cream sales is the response because the ice cream sales could explain the city's temperature. 
B) Temperature is the explanatory variable and ice cream sales is the response because a city's temperature could explain the amount of ice cream sales. 
C) Ice cream sales is the explanatory variable and temperature is the response because a city's temperature could explain the amount of ice cream sales. 
D) Ice cream sales is the explanatory variable and temperature is the response because the ice cream sales could explain the city's temperature. 
A) Temperature is the explanatory variable and ice cream sales is the response because the ice cream sales could explain the city's temperature. 
B) Temperature is the explanatory variable and ice cream sales is the response because a city's temperature could explain the amount of ice cream sales. 
C) Ice cream sales is the explanatory variable and temperature is the response because a city's temperature could explain the amount of ice cream sales. 
D) Ice cream sales is the explanatory variable and temperature is the response because the ice cream sales could explain the city's temperature.

Question 5

Which of the following statements regarding the correlation coefﬁcient is true?

Accepted Answer

A) The correlation coefﬁcient is a value between 0 and 1. 
B) A high correlation coefﬁcient tells us the data are linear. 
C) A correlation coefﬁcient of 0 means that two variables are perfectly linearly related. 
D) A correlation coefﬁcient of −1 means that as one variable increases, the other decreases. 
A) The correlation coefﬁcient is a value between 0 and 1. 
B) A high correlation coefﬁcient tells us the data are linear. 
C) A correlation coefﬁcient of 0 means that two variables are perfectly linearly related. 
D) A correlation coefﬁcient of −1 means that as one variable increases, the other decreases.

Question 6

Use the following information for following questions .
A random sample of 100 cars was taken and data were recorded on the miles per gallon (mpg) in the city
and on the highway. The mean city mpg was 28 with a standard deviation of 9.2. The mean highway mpg
was 35 with a standard deviation of 8.6. The correlation coefﬁcient between city mpg and highway mpg is
-Determine the correct value of the slope for the linear model that predicts highway mpg from city mpg and interpret it in context.

Accepted Answer

A) The slope is 0.888.For every one mpg increase in city mpg, the highway mpg is predicted to increase by 0.888. 
B) The slope is 0.888.For every one mpg increase in highway mpg, the city mpg is predicted to increase by 0.888. 
C) The slope is 1.016.For every one mpg increase in city mpg, the highway mpg is predicted to increase by 1.016. 
D) The slope is 1.016.For every one mpg increase in highway mpg, the city mpg is predicted to increase by 1.016. 
A) The slope is 0.888.For every one mpg increase in city mpg, the highway mpg is predicted to increase by 0.888. 
B) The slope is 0.888.For every one mpg increase in highway mpg, the city mpg is predicted to increase by 0.888. 
C) The slope is 1.016.For every one mpg increase in city mpg, the highway mpg is predicted to increase by 1.016. 
D) The slope is 1.016.For every one mpg increase in highway mpg, the city mpg is predicted to increase by 1.016.

Question 7

Create a data set of 2 variables (X and Y) such that the relationship between X and Y would have a perfect negative correlation of −1.Note: The data set can be very small (three to four X and Y values).

Accepted Answer

Answers ma

Question 8

For the following scatterplot, what effect would the outlier have on the slope of the regression equation? Explain your reasoning.

Accepted Answer

The outlier would decrease the slope bec

Question 9

Given the following scatterplot, if the point in the upper right corner were removed, what will happen to the value of the correlation coefﬁcient, r?

Accepted Answer

A) r will get closer to 1. 
B) r will get closer to 0. 
C) r will get closer to −1. 
D) r will not change. 
A) r will get closer to 1. 
B) r will get closer to 0. 
C) r will get closer to −1. 
D) r will not change.

Question 10

Use the following information for following questions .
The following scatterplot shows the relationship between heights (in cm) and weights (in kg) of 100
Americans. The coefﬁcient of determination was found to be 37.9%.  
-Calculate the value of the correlation coefﬁcient between height and weight.

Accepted Answer

The answer of Use the following information for following questions...

Question 11

For any set of data, the regression equation will always pass through

Accepted Answer

A) The point that represents the mean value of x and the mean value of y. 
B) Every point in the data set. 
C) At least two points in the data set. 
D) The intercept and the slope. 
A) The point that represents the mean value of x and the mean value of y. 
B) Every point in the data set. 
C) At least two points in the data set. 
D) The intercept and the slope.

Question 12

A study in the Los Angeles Times reported that the number of liquor stores in a neighborhood has a strong positive linear association with the amount of crime in that neighborhood. What can you determine about the relationship between the number of liquor stores and the amount of crime?

Accepted Answer

A) No conclusions can be drawn without seeing a scatterplot of the data. 
B) People who live in neighborhoods with more liquor stores commit more crimes. 
C) Neighborhoods with a higher number of liquor stores tend to have a higher amount of crimes. 
D) If we decrease the number of liquor stores in a neighborhood, the amount of crimes will decrease. 
A) No conclusions can be drawn without seeing a scatterplot of the data. 
B) People who live in neighborhoods with more liquor stores commit more crimes. 
C) Neighborhoods with a higher number of liquor stores tend to have a higher amount of crimes. 
D) If we decrease the number of liquor stores in a neighborhood, the amount of crimes will decrease.

Question 13

What effect would an outlier have on the slope of a regression equation?

Accepted Answer

A) An outlier has no effect on a regression equation. 
B) An outlier could either increase or decrease the slope, depending on its location. 
C) An outlier always decreases the slope. 
D) An outlier always increases the slope. 
A) An outlier has no effect on a regression equation. 
B) An outlier could either increase or decrease the slope, depending on its location. 
C) An outlier always decreases the slope. 
D) An outlier always increases the slope.

Question 14

Use the following regression equation regarding airline tickets for following questions .   Note that Distance is the amount of miles between the departure and arrival cities, and Price is the
cost of an airline ticket.
-Interpret the slope of the regression equation in the context of the data.

Accepted Answer

The slope is 0.22. For every a

Question 15

Which of the following sets of numbers would result in a positive correlation of 1?

Accepted Answer

A)   
B)   
C)   
D)   
A)   
B)   
C)   
D)

Question 16

Use the following information to answer Questions .
The scatterplot below shows the relationship between the average monthly temperature and the
monthly cost of a gas bill. The correlation coefﬁcient between the values is −0.92.  
-Do lower monthly temperature cause gas bills to be more expensive? Explain your reasoning.

Accepted Answer

No, lower monthly temperatures do not ca

Question 17

A study about exercise routines reported that the amount of time a person spends working out has a strong positive linear association with the amount of weight he/she loses. What can you determine about the relationship between amount of time spent at the gym and the amount of weight a person loses?

Accepted Answer

Answers may vary. Ex

Question 18

[Objective: Interpret the coefficient of determination in context.] Suppose the correlation coefficient describing how the heights of teenage boys predicts their weights is 0.85. What is the coefficient of determination   and what does it mean in context?

Accepted Answer

A)    of the variation in heights of teenage boys can be explained by their weight. 
B)    of the variation in weights of teenage boys can be explained by their height. 
C)    is 0.85 .85% of the variation in heights of teenage boys can be explained by their weight. d.   is 0.85 .85% of the variation in weights of teenage boys can be explained by their height. 
A)    of the variation in heights of teenage boys can be explained by their weight. 
B)    of the variation in weights of teenage boys can be explained by their height. 
C)    is 0.85 .85% of the variation in heights of teenage boys can be explained by their weight. d.   is 0.85 .85% of the variation in weights of teenage boys can be explained by their height.

Question 19

Suppose data were collected on neighborhoods about the number of crimes committed and the number of police who patrol the area. Which variable is the explanatory variable and which one is the response? Ex- plain your reasoning.

Accepted Answer

There are two possible answers here: (1)

Which scatterplot below depicts a stronger linear relationship? Why?

Which scatterplot below depicts a stronger linear relationship? Why? Explain what the scatterplot shows regarding a tree's volume.

Suppose temperatures and monthly ice cream sales were measured for 100 randomly selected cities. Which variable is the explanatory variable and which one is the response?

Which of the following statements regarding the correlation coefﬁcient is true?

Create a data set of 2 variables (X and Y) such that the relationship between X and Y would have a perfect negative correlation of −1.Note: The data set can be very small (three to four X and Y values).

For the following scatterplot, what effect would the outlier have on the slope of the regression equation? Explain your reasoning.

Given the following scatterplot, if the point in the upper right corner were removed, what will happen to the value of the correlation coefﬁcient, r?

For any set of data, the regression equation will always pass through

A study in the Los Angeles Times reported that the number of liquor stores in a neighborhood has a strong positive linear association with the amount of crime in that neighborhood. What can you determine about the relationship between the number of liquor stores and the amount of crime?

What effect would an outlier have on the slope of a regression equation?

Use the following regression equation regarding airline tickets for following questions . Note that Distance is the amount of miles between the departure and arrival cities, and Price is the cost of an airline ticket. -Interpret the slope of the regression equation in the context of the data.

Which of the following sets of numbers would result in a positive correlation of 1?

A study about exercise routines reported that the amount of time a person spends working out has a strong positive linear association with the amount of weight he/she loses. What can you determine about the relationship between amount of time spent at the gym and the amount of weight a person loses?

[Objective: Interpret the coefficient of determination in context.] Suppose the correlation coefficient describing how the heights of teenage boys predicts their weights is 0.85. What is the coefficient of determination and what does it mean in context?

Suppose data were collected on neighborhoods about the number of crimes committed and the number of police who patrol the area. Which variable is the explanatory variable and which one is the response? Ex- plain your reasoning.

Introduction to Data

Picturing Variation With Graphs

Numerical Summaries of Center and Variation

Modeling Variation With Probability

Modeling Random Events: the Normal and Binomial Models

Survey Sampling and Inference

Hypothesis Testing for Population Proportions

Inferring Population Means

Associations Between Categorical Variables

Multiple Comparisons and Analysis of Variance

Experimental Design: Controlling Variation

Inference Without Normality

Inference for Regression

Filters

Exam 4: Regression Analysis: Exploring Associations Between Variables

Which scatterplot below depicts a stronger linear relationship? Why?

Which scatterplot below depicts a stronger linear relationship? Why? Explain what the scatterplot shows regarding a tree's volume.

Suppose temperatures and monthly ice cream sales were measured for 100 randomly selected cities. Which variable is the explanatory variable and which one is the response?

Which of the following statements regarding the correlation coefﬁcient is true?

Create a data set of 2 variables (X and Y) such that the relationship between X and Y would have a perfect negative correlation of −1.Note: The data set can be very small (three to four X and Y values).

For the following scatterplot, what effect would the outlier have on the slope of the regression equation? Explain your reasoning.

Given the following scatterplot, if the point in the upper right corner were removed, what will happen to the value of the correlation coefﬁcient, r?

For any set of data, the regression equation will always pass through

A study in the Los Angeles Times reported that the number of liquor stores in a neighborhood has a strong positive linear association with the amount of crime in that neighborhood. What can you determine about the relationship between the number of liquor stores and the amount of crime?

What effect would an outlier have on the slope of a regression equation?

Use the following regression equation regarding airline tickets for following questions . Note that Distance is the amount of miles between the departure and arrival cities, and Price is the cost of an airline ticket. -Interpret the slope of the regression equation in the context of the data.

Which of the following sets of numbers would result in a positive correlation of 1?

[Objective: Interpret the coefficient of determination in context.] Suppose the correlation coefficient describing how the heights of teenage boys predicts their weights is 0.85. What is the coefficient of determination and what does it mean in context?

Suppose data were collected on neighborhoods about the number of crimes committed and the number of police who patrol the area. Which variable is the explanatory variable and which one is the response? Ex- plain your reasoning.

Introduction to Data

Picturing Variation With Graphs

Numerical Summaries of Center and Variation

Modeling Variation With Probability

Modeling Random Events: the Normal and Binomial Models

Survey Sampling and Inference

Hypothesis Testing for Population Proportions

Inferring Population Means

Associations Between Categorical Variables

Multiple Comparisons and Analysis of Variance

Experimental Design: Controlling Variation

Inference Without Normality

Inference for Regression

Filters