Deck 9: Correlation and Regression
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Deck 9: Correlation and Regression
1
The standard error of estimate is the square root of the unexplained variation.
True
2
A regression line can be used to show trends in data.
True
3
Regression is a statistical method used to describe the nature of the relationship between variables.
True
4
The two variables in a scatter plot are called the
A) Independent variable and dependent variable
B) Relative frequency and relative proportion
C) Spread and pattern
D) Lines and points
A) Independent variable and dependent variable
B) Relative frequency and relative proportion
C) Spread and pattern
D) Lines and points
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5
If the correlation between two variables is computed to be 0.012, one can conclude that there is
essentially no relation between the two variables.
essentially no relation between the two variables.
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6
If one found that the sum of the residuals from a regression line (with an intercept) was a large negative
value, one could conclude that there is a negative relationship between the independent and dependent
variables.
There must have been a calculation error since the residuals sum to 0 (apart from rounding error).
value, one could conclude that there is a negative relationship between the independent and dependent
variables.
There must have been a calculation error since the residuals sum to 0 (apart from rounding error).
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7
A positive relationship exists when both variables increase or decrease at the same time.
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8

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9
The standard error of estimate is the standard deviation of the observed x-values about the predicted
values.

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10
Using a regression line of
, a value of x = 3.6 would result in a predicted value of
.


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11
When the x-axis and y-axis have been truncated, the y-intercept can be used to graph the regression
line.
line.
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12
The range of the correlation coefficient is from 0 to 1.
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13
A regression line was calculated as
. The slope of this line is -3.2.

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14
The symbol used for the multiple correlation coefficient is R.
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15
With enough variables, it is possible to get an
value close to 1, even if the variables have no particular
meaning in the model.

meaning in the model.
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16
The population correlation coefficient is computed by using all possible pairs of data values x, y taken
from a population.
from a population.
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17
The rounding rule for the correlation coefficient uses two decimal places.
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18
The possible relationship between pairs of data values could be examined from a
A) Histogram
B) Scatter plot
C) Pareto graph
D) Pie chart
A) Histogram
B) Scatter plot
C) Pareto graph
D) Pie chart
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19
A positive linear relationship exists when the points in a Pareto graph fall approximately in an ascending
straight line.
straight line.
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20
A correlation coefficient of 0.96 would mean that the values of x increase as the values of y decrease.
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21

A) 0.942
B) -0.347
C) -0.496
D) -0.992
F
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22
Daniel Wiseman, a scientist for Gres-Trans Corp., wants to determine if the flow rate of a particular material changes with different changes in temperature. The data is plotted in the figure
Below. What type of relationship exists between the flow rate and the change in temperature?

A) negative
B) positive
C) There is no relationship.
D) curvilinear
Below. What type of relationship exists between the flow rate and the change in temperature?

A) negative
B) positive
C) There is no relationship.
D) curvilinear
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23


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24

A) Do not reject -= 0 because -4.31 < 3.18
B) Reject -= 0 because -3.99 > 3.18
C) Do not reject -= 0 because -3.99 > -4.30
D) Reject -= 0 because -4.31 > 2.78
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25

Compute the test value for the data in the table.
A) 8.329
B) 6.785
C) 5.919
D) 9.648
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26

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27

If a correlation coefficient calculated for n = 14 and

A) 4.059
B) 5.736
C) 2.851
D) 6.374
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28

A) -0.484
B) 0.235
C) 0.000
D) -0.323
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29

A) 0.762
B) 0.857
C) 0.679
D) 0.932
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30

A) -0.683
B) 0.197
C) 1.000
D) -1.369
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31

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32
Which of the following does not explain a possible relationship between variables when the null hypothesis is rejected?
A) direct cause-and-effect
B) reverse cause-and-effect
C) caused by a third variable
D) negative effect
A) direct cause-and-effect
B) reverse cause-and-effect
C) caused by a third variable
D) negative effect
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33

A) 13,251
B) 93,624
C) 19,712
D) 9349
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34

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35

A) 0.123
B) 10.857
C) 0.001
D) 0.082
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36

A) 13,251
B) 93,624
C) 19,712
D) 9349
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37

A) 0.661
B) -0.437
C) 0.467
D) -0.135
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38

Compute the value of the correlation coefficient for the data in the table.
A) 0.924
B) 0.834
C) 0.798
D) 0.938
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39

A) positive
B) negative
C) multiple
D) There is no relationship.
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40

A) 0.521
B) 0.368
C) -0.271
D) -0.058
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41
If the equation for the regression line is y = 7x - 6, then a value of x = 3 will result in a predicted value for y of
A) 13
B) 25
C) 27
D) 15
A) 13
B) 25
C) 27
D) 15
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42

A) 3.54
B) 3.87
C) 4.15
D) 4.87
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43

A) 6.36
B) 7.34
C) 8.75
D) 5.49
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44
If the equation for the regression line is y = -4x + 6, then the slope of this line is
A) 12
B) 6
C) 2
D) -4
A) 12
B) 6
C) 2
D) -4
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45
If the correlation coefficient is 0.93, what is the unexplained variation?
A) 7%
B) 93%
C) 13.5%
D) 86.5%
A) 7%
B) 93%
C) 13.5%
D) 86.5%
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46

A) -1.93
B) -0.93
C) 1.36
D) -4.78
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47
The equation of a regression line is
. What is the intercept of this line?
A) -4.6
B) 3.2
C) 4.6
D) 0

A) -4.6
B) 3.2
C) 4.6
D) 0
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48
If the equation for the regression line is y = -8x + 3, then the intercept of this line is
A) 6
B) 3
C) -5
D) -8
A) 6
B) 3
C) -5
D) -8
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49
If the correlation coefficient r is equal to 0.48, find the coefficient of determination.
A) 0.77
B) 0.69
C) 0.36
D) 0.23
A) 0.77
B) 0.69
C) 0.36
D) 0.23
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50

A) 11.50
B) 3.80
C) 14.46
D) 7.35
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51
If the equation for the regression line is y = 11x + 2, then a value of x = -3 will result in a predicted value for y of
A) 2
B) 5
C) -31
D) 11
A) 2
B) 5
C) -31
D) 11
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52
What is the value of
when x = 3, if the equation of the regression line is 
A) 4.73
B) 5.29
C) 34.5
D) 11.7


A) 4.73
B) 5.29
C) 34.5
D) 11.7
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53
If the correlation coefficient r is equal to 0.6, find the coefficient of nondetermination.
A) 0.64
B) 0.77
C) 0.48
D) 0.36
A) 0.64
B) 0.77
C) 0.48
D) 0.36
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54

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55

A) 0.71
B) 3.72
C) 3.93
D) 9.32
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56
If the correlation coefficient is 0.79, what is the explained variation?
A) 37.6%
B) 62.4%
C) 79%
D) 21%
A) 37.6%
B) 62.4%
C) 79%
D) 21%
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57
If the correlation coefficient r is equal to 0.66, find the coefficient of determination.
A) The coefficient of determination is 0.56.
B) The coefficient of determination is 0.81.
C) The coefficient of determination is 0.44.
D) The coefficient of determination is 0.19.
A) The coefficient of determination is 0.56.
B) The coefficient of determination is 0.81.
C) The coefficient of determination is 0.44.
D) The coefficient of determination is 0.19.
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58

A) -0.51
B) -1.43
C) 1.01
D) -3.37
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59

A) 1.38
B) 2.90
C) 3.77
D) 7.54
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60

A) -1.31
B) -0.43
C) 0.93
D) -3.06
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61
Two researchers run identical experiments, except researcher A collects twice as many points as researcher B. For a specific value of x, researcher A estimates a y value of
, and researcher B
Estimates a y value of
. We would expect that researcher A's 95% prediction interval around
to be,
In general,
A) wider than researcher B's 95% prediction interval around
B) narrower than researcher B's 95% prediction interval around
C) the same as researcher B's 95% prediction interval around
D) wider than researcher B's 95% prediction interval around
or narrower than researcher B's 95%
) prediction interval around
, with equal probability

Estimates a y value of


In general,
A) wider than researcher B's 95% prediction interval around

B) narrower than researcher B's 95% prediction interval around

C) the same as researcher B's 95% prediction interval around

D) wider than researcher B's 95% prediction interval around

) prediction interval around

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62

A) 3.36
B) 3.93
C) 7.06
D) 9.07
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63
The standard error of estimate can be used for constructing a(n) __________ interval about a
value.
________________________________________

________________________________________
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64
When r is not significantly different from 0, the best predictor of y is the mean of the __________ of
y.
________________________________________
y.
________________________________________
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65
In a multiple regression model
then the predicted value for y will change by
A) 10
B) 32
C) 0
D) 30

A) 10
B) 32
C) 0
D) 30
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66
A study on the oxygen consumption rate (OCR) of sea cucumbers involved random samples of size 3 at each of the temperatures 10, 11, 12, 13, 14, and 15oC A regression model was fit in order to study
The relationship between OCR and temperature. If one of the analysts converted the temperatures to
Fahrenheit
the correlation coefficient would be 
The relationship between OCR and temperature. If one of the analysts converted the temperatures to
Fahrenheit


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67
An analysis results in a multiple regression equation of
We can conclude that
A) The variable
is a very significant factor in this model
B) The variable
is a moderately significant factor in this model
C) The variable
is not a significant factor in this model
D) This is insufficient information to assess the significance of

A) The variable

B) The variable

C) The variable

D) This is insufficient information to assess the significance of

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68
For a prediction value of y' from a specific value x, which of the following contribute to the prediction error?
A) The error in estimating the slope
B) The error in estimating the intercept
C) The standard error of the estimate
D) All of the above
A) The error in estimating the slope
B) The error in estimating the intercept
C) The standard error of the estimate
D) All of the above
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69
__________ is a statistical method used to determine whether a relationship between variables exists.
________________________________________
________________________________________
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70
A study on the oxygen consumption rate (OCR) of sea cucumbers involved random samples of size 3 at each of the temperatures 10, 11, 12, 13, 14, and 15oC A regression model was fit in order to study
The relationship between OCR and temperature. The degrees of freedom for testing that there is no
Relationship between OCR and temperature would be
A) 5
B) 8
C) 15
D) 16
The relationship between OCR and temperature. The degrees of freedom for testing that there is no
Relationship between OCR and temperature would be
A) 5
B) 8
C) 15
D) 16
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71

A) 0.66
B) 1.02
C) 1.49
D) 1.79
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72

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73
A study on the oxygen consumption rate (OCR) of sea cucumbers involved random samples of size 3 at each of the temperatures 10, 11, 12, 13, 14, and
. A regression model was fit in order to study the
Relationship between OCR and temperature. The slope of the regression line was found to be positive.
If one of the analysts converted the temperatures to Fahrenheit
the slope of the
Regression line would be

Relationship between OCR and temperature. The slope of the regression line was found to be positive.
If one of the analysts converted the temperatures to Fahrenheit

Regression line would be

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74
A correlation coefficient r was calculated to be 0.61. The coefficient of determination would be
approximately __________.
________________________________________
approximately __________.
________________________________________
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75

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76
In a __________ relationship, as one variable increases, the other variable decreases, and vice versa.
________________________________________
________________________________________
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77
If there is a strong negative linear relationship between the variables, the value of __________ will be
close to -1.
________________________________________
close to -1.
________________________________________
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78
A multiple regression line was calculated in which
was a student's grade point average and
was a student's age. The multiple regression line was calculated as
. If a student has a grade
Point average of 5.9 and is 20 years old, what is the predicted value of
?
A) 387.2
B) 400.1
C) 421.6
D) 615.5



Point average of 5.9 and is 20 years old, what is the predicted value of

A) 387.2
B) 400.1
C) 421.6
D) 615.5
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79
As a researcher collects more and more data, the 95% prediction intervals in general
A) become narrower and narrower, with the widths getting closer and closer to 0
B)become narrower and narrower, but the widths are always more than approximately 2 times the standard error of the estimate
C)become narrower and narrower, but the widths are always more than approximately 4 times the standard error of the estimate
D) become narrower and narrower, but the widths are always more than approximately 4 times the slope
A) become narrower and narrower, with the widths getting closer and closer to 0
B)become narrower and narrower, but the widths are always more than approximately 2 times the standard error of the estimate
C)become narrower and narrower, but the widths are always more than approximately 4 times the standard error of the estimate
D) become narrower and narrower, but the widths are always more than approximately 4 times the slope
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80
In a multiple regression model
if the value of
increases by 6 and the value of x3 decreases by 3, then the predicted value for y will
A) increase by 87
B) decrease by 87
C) increase by 45
D) decrease by 45


A) increase by 87
B) decrease by 87
C) increase by 45
D) decrease by 45
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