AnswersStatistical ReasoningStatistics as a Problem-Solving Process and the Role of Questioning

Statistics as a Problem-Solving Process and the Role of Questioning — Test Answers

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1
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The equation hat y is equal to 17 point 4 plus 0 point 5 x is called the least-squares regression line because it

A
makes the strongest association between weight and height.
B
minimizes the sum of the squared distances from the actual y -value to the predicted y -value.
C
maximizes the sum of the squared distances from the actual y -value to the predicted y -value.
D
is least able to make accurate predictions for the data.
2
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The arm span and foot length were both measured (in centimeters) for each of 20 students in a biology class. The computer output displays the regression analysis. Open image in full-screen view Which of the following is the best interpretation of the coefficient of determination r squared ?

A
About 63 percent of the variation in foot length is accounted for by the linear relationship formed with the arm span.
B
About 65 percent of the variation in foot length is accounted for by the linear relationship formed with the arm span.
C
About 63 percent of the variation in arm span is accounted for by the linear relationship formed with the foot length.
D
About 37 percent of the variation in arm span is accounted for by the linear relationship formed with the foot length.
4

Water is poured into a large, cone-shaped cistern. The volume of water, measured in cm cubed , is reported at different time intervals, measured in seconds. The scatterplot of volume versus time showed a curved pattern. Which of the following would linearize the data for volume and time?

A
the natural log of Seconds , cm cubed
B
the natural log of Seconds , the natural log of open paren cm cubed close paren
C
Seconds , the natural log of open paren cm cubed close paren
D
Seconds , cm cubed
5

A sports statistician was interested in the relationship between game attendance (in thousands) and the number of wins for baseball teams. Information was collected on several teams and was used to obtain the regression equation widehat y is equal to 4 point 9 x plus 15 point 2 , where x represents attendance (in thousands) and widehat y is the predicted number of wins. Which statement best describes the meaning of the slope of the regression line?

A
For each increase in attendance by 1 comma 000 , the predicted number of wins increases by 4 point 9 .
B
For each increase in the number of wins by 1 , the predicted attendance increases by 15 comma 200 .
C
For each increase in the number of wins by 1 , the predicted attendance increases by 4 comma 900 .
D
For each increase in attendance by 1 comma 000 , the predicted number of wins increases by 15 point 2 .
7

Market researchers were interested in the relationship between the number of pieces in a brick-building set and the cost of a set. Information was collected from a survey and was used to obtain the regression equation widehat y is equal to 0 point 0 8 x plus 1 point 2 0 , where x represents the number of pieces in a set and widehat y is the predicted price (in dollars) of a set. Which statement best describes the meaning of the y - intercept of the regression line?

A
When the number of pieces is 0 , the predicted price is 0 point 0 8 dollars . This interpretation is not meaningful because a set cannot have 0 pieces.
B
When the price of a set is 0 dollars , the predicted number of pieces is 1 point 2 0 .
C
When the price of a set is 0 dollars , the predicted number of pieces is 0 .
D
When the number of pieces is 0 , the predicted price is 1 point 2 0 dollars . This interpretation is not meaningful because a set cannot have 0 pieces.
8

Based on the scatterplots, which type of model is most suitable for estimating the stock price?

A
An exponential model is suitable because the scatterplot of log(weeks) against log(stock price) shows a curved relationship.
B
A linear model is suitable because the scatterplot of weeks against log(stock price) shows a strong linear relationship.
C
A power model is suitable because the scatterplot of log(weeks) against log(stock price) shows a curved relationship.
D
An exponential model is suitable because the scatterplot of weeks against log(stock price) shows a strong linear relationship.
9

Which statement regarding the association shown could explain the relationship?

A
Schools in more affluent areas have larger class sizes, which is associated with higher test scores.
B
Schools in less affluent areas tend to have smaller class sizes, which is associated with lower test scores.
C
Class size appears to have little effect on test scores.
D
Schools in more affluent areas have smaller class sizes, which is associated with higher test scores.
10

Using the computer output, what is the correlation?

A
0 point 6 3 0
B
0 point 7 9 4
C
0 point 8 0 6
D
0 point 6 4 9
11

What effect does the circled point have on the slope and y - intercept of the least-squares regression line?

A
This point will decrease the value of the slope and increase the value of the y - intercept.
B
This point will decrease the value of the slope and decrease the value of the y - intercept.
C
This point will increase the value of the slope and decrease the value of the y - intercept.
D
This point will increase the value of the slope and increase the value of the y - intercept.
12

What is the equation of the least-squares regression line?

A
the natural log of widehat Time is equal to negative 0 point 1 0 1 plus 2 point 3 0 5 times Element
B
the natural log of widehat Element is equal to 2 point 3 0 5 minus 0 point 1 0 1 times Time
C
the natural log of widehat Element is equal to negative 0 point 1 0 1 plus 2 point 3 0 5 times Time
D
widehat Element is equal to 2 point 3 0 5 minus 0 point 1 0 1 ln Time
13

Based on the residual plot, is the linear model appropriate?

A
Yes, there is no clear pattern in the residual plot.
B
No, there is no clear pattern in the residual plot.
C
No, there are no homes between 2 comma 300 and 2 comma 900 square feet.
D
Yes, half of the residuals are positive and half are negative.
14

Which of the following is an accurate description of the scatterplot?

A
The more seeds that are planted per square foot, the smaller the expected yield of the crop.
B
The more seeds that are planted per square foot, the larger the expected yield of the crop.
C
The expected yield of a crop is high whenever the number of seeds planted per square foot is small or large. A larger yield is expected when the number of seeds per square foot is around 60.
D
The expected yield of a crop is low whenever the number of seeds planted per square foot is small or large. A larger yield is expected when the number of seeds per square foot is around 60.
15

Which of the following statements is false?

A
The difference between percent of students living on or off campus decreases as number of years of college increases.
B
The largest percentage of students living on campus is in the 1st-year group.
C
As the number of years in college increases, the percentage of students living off campus increases.
D
As the number of years in college increases, the percentage of students living on campus increases.
16

Based on the scatterplot and the residual plot, is a linear model appropriate for predicting the Short Program score from the Free Skate score?

A
A linear model is appropriate because the scatterplot is roughly linear, and the residual plot does not show a clear pattern.
B
A linear model is not appropriate because there are outliers in the scatterplot.
C
A linear model is not appropriate because the residual plot does not show a linear pattern.
D
A linear model is appropriate because the residuals are centered about zero.
17

Which of the following is true, according to the graph?

A
There is a much smaller preference for math among those who prefer country.
B
There is a much larger preference for science among those who prefer R&B.
C
The percentages for class preference are relatively the same among the different music groups.
D
There is a much larger preference for English among those who prefer rock.
18

Which scatterplot represents the student data?

A
Image with description A scatter plot titled high school and college G P A has College G P A on the x-axis, and H S G P A on the y-axis. Points are at (2.8, 2.5), (2.9, 2.25), (2.9, 3.5), (3, 2.5), (3, 3), (3, 3.25), (3, 3.5), (3, 4), (3.1, 3.25), (3.1, 3.5), (3.1, 4), (3.2, 3.25).
B
Image with description A scatter plot titled high school and college G P A has College G P A on the x-axis, and H S G P A on the y-axis. Points are at (2.8, 2.5), (2.9, 2.25), (2.9, 3.5), (3, 2.5), (3, 3), (3, 3.25), (3, 3.5), (3, 4), (3.1, 3.5), (3.1, 4), (3.2, 3.25).
C
Image with description A scatter plot titled high school and college G P A has H S G P A on the x-axis, and College G P A on the y-axis. Points are at (3.25, 3.2), (3.5, 3.0), (3.5, 2.9), (3.25), (3.0), (2.5, 3.0), (4, 3.0), (4, 3.1), (3.5, 3.1), (3.25, 3.1), (3.25, 3.1), (3.5, 3.0), (3.5, 3.0), (4, 3.1), (3, 3.0), (3.5, 3.1), (2.25, 2.9), (2.5, 2.8).
D
Image with description A scatter plot titled high school and college G P A has H S G P A on the x-axis, and College G P A on the y-axis. Points are at (3.25, 3.2), (3.5, 3.0), (3.5, 2.9), (3.25), (3.0), (2.5, 3.0), (4, 3.0), (4, 3.1), (3.5, 3.1), (3.25, 3.1), (3.25, 3.1), (3.5, 3.0), (3.5, 3.0), (4, 3.1), (3, 3.0), (3.5, 3.1), (2.25, 2.9), (2.5, 2.8), (4, 3.2).
19

Which of the following is an accurate description of the scatterplot?

A
The kickers have unusually high success rates when the distance is small.
B
As the distance of the attempt increases, the kickers have a lower success rate for their field goals.
C
The kickers have unusually low success rates when the distance is large.
D
As the distance of the attempt increases, the kickers tend to have a lower success rate for their field goals.
20

The equation of the least-squares regression line is hat y is equal to 68 point 5 plus 11 point 4 x , where hat y is the number of students enrolled and x is number of years the school has been open. Which shows the residual plot?

A
Image with description A dot plot with the x axis titled Number of years begins with 0 and ends at 8 with equal intervals of 2, such as 0, 2, 4, 6, and 8. The y axis titled Residual begins with negative 15 and ends at 20 with equal intervals of 5, such as negative 15, negative 10, negative 5, 0, 5, 10, 15, and 20. A horizontal line parallel to the x axis starts from the point where y is 0. There is 1 dot at approximately 1, 12; 1 dot at 2, 3; 1 dot at 3, negative 3; 1 dot at 4, negative 10; 1 dot at 5,negative 12; 1 dot at 6, negative 6, 1 dot at 7, negative 1; and 1 dot at 8, 16.
B
Image with description A dot plot with the x axis titled Number of years begins with 0 and ends at 8 with equal intervals of 2, such as 0, 2, 4, 6, and 8. The y axis titled Residual begins with negative 80 and ends at 20 with equal intervals of 20, such as negative 80, negative 60, negative 40, negative 20, 0, and 20. A horizontal line parallel to the x axis starts from the point where y is 0. There is 1 dot at approximately 1, 18; 1 dot at 2, 16; 1 dot at 3, 10; 1 dot at 4, 5; 1 dot at 5, negative 2; 1 dot at 6, negative 22, 1 dot at 7, negative 39; and 1 dot at 8, negative 70.
C
Image with description A dot plot with the x axis titled Number of years begins with 0 and ends at 8 with equal intervals of 2, such as 0, 2, 4, 6, and 8. The y axis titled Residual begins with negative 20 and ends at 15 with equal intervals of 5, such as negative 20, negative 15, negative 10, negative 5, 0, 5, 10, and 15. A horizontal line parallel to the x axis starts from the point where y is 0. There is 1 dot at approximately 1, negative 12; 1 dot at 2, negative 3; 1 dot at 3, 3; 1 dot at 4, 10; 1 dot at 5, 12; 1 dot at 6, 6, 1 dot at 7, 1; and 1 dot at 8, -16.
D
Image with description A dot plot with the x axis titled Number of years begins with 0 and ends at 8 with equal intervals of 2, such as 0, 2, 4, 6, and 8. The y axis titled Residual begins with negative 20 and ends at 80 with equal intervals of 20, such as negative 20, 0, 20, 40, 60, and 80. A horizontal line parallel to the x axis starts from the point where y is 0. There is 1 dot at approximately 1, negative 18; 1 dot at 2, negative 16; 1 dot at 3, negative 10; 1 dot at 4, negative 5; 1 dot at 5, 5; 1 dot at 6, 22, 1 dot at 7, 38, and 1 dot at 8, 75.

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