Question number 1.
Your answer was B. Correct. Which of the following would be the scatterplot for the given data?
x
3 7 11 11 16 16 y
23 28 26 40 34 41 A
B
C
D
E
None of the above
Question number 2.
Your answer was A. Correct. What can be said about the relationship between the explantory variable and the response variable in the following scatterplot?
A
There is a strong negative linear association.
B
The explanatory variable causes the responses.
C
There is a weak negative linear association.
D
There is a strong positive linear association.
E
None of the above
Question number 3.
Your answer was E. Correct. Determine the correlation coefficient for the data shown in this table:
x
5 5 9 12 16 16 y
43 38 30 22 18 11 A
0.9726
B
0.9460
C
−
0.9460
D
−
0.4863
E
−
0.9726
F
None of the above
Question number 4.
Your answer was D. Correct. Choose the best correlation coefficient for the data shown in this scatterplot:
A
−
0.3317
B
0.3317
C
−
0.6634
D
0.6634
E
1.4664
Question number 5.
Your answer was E. Correct. Which of the following is a true statement?
A
The variable that is being predicted in regression analysis is the independent variable.
B
If there is no correlation between the independent and dependent variables, then the value of the correlation coefficient must be -1.
C
A negative correlation indicates that as values of x
decrease, values of y
will decrease.
D
The coefficient of determination can assume negative values.
E
The correlation coefficient r
is always between -1 and +1.
F
None of the above
Question number 6.
Your answer was A. Correct. The decline of salmon fisheries along the Columbia River in Oregon has caused great concern among commercial and recreational fishermen. The paper 'Feeding of Predaceous
Fishes on Out-Migrating Juvenile Salmonids in John Day Reservoir, Columbia River' (Trans. Amer. Fisheries Soc. (1991: 405-420)) gave the accompanying data on y = maximum
size of salmonids consumed by a northern squaw fish (the most abundant salmonid predator) and x = squawfish length, both in mm. Use the following statistics to give the equation
of the least squares regression line.
x
= 525.160, y
= 482.534, s
x
= 11.112, s
y
= 12.400, r
= 0.9768
A
ŷ
= 1.090
x
−
89.890
B
ŷ
= 1.090
x
+ 89.890
C
ŷ
= 0.875
x
−
89.890
D
ŷ
= 0.875
x
+ 89.890
E
ŷ
= −
89.890
x
+ 1.090
F
None of the above
Question number 7.
Your answer was A. Correct. Suppose that you are given the following results. Find the correlation coefficient of the data.
s
x
= 1.867, s
y
= 14.100, b
= −
6.540
A
−
0.866
B
−
0.433
C
−
0.155
D
0.866
E
0.155
F
None of the above
Question number 8.
Your answer was A. Correct. Suppose you find that the correlation coefficient for a set of data is −
0.849. What is the coefficient of determination and what does it mean?
A
0.721; This means that 72.1%% of the variation of y
is explained by the LSRL of y
on x
.
B
−
0.849; This means that we are 84.9%% accurate with our prediction of the LSRL equation.
C
0.849; This means that 84.9%% of the variation of y
is explained by the LSRL of y
on x
.
D
0.721; This means that we are 72.1%% accurate with our prediction of the LSRL equation.
E
None of the above
Question number 9.
Your answer was D. Correct. Suppose that the LSRL for the appraised value (in thousands of dollars) and number of rooms for houses in East Meadow, New York is ŷ
= 19.718
x
+ 74.80. Predict the price of a 11
room house (in thousands of dollars).
tbl
A
399.698
B
3208.678
C
296.698
D
291.698
E
409.698
F
None of the above
Question number 10.
Your answer was A. Correct. Select the equation of the least squares line for the data: (51.00, .6), (48.75, 1.5), (52.50, .3), (46.50, 3.0), (45.00, 2.7), (41.25, 3.9), (43.50, 3.0).
A
ŷ
= 17.374 −
0.32440
x
B
ŷ
= -17.374 −
0.32440
x
C
ŷ
= 0.32440
x
−
17.374
D
ŷ
= 19.111 −
0.35684
x
E
ŷ
= 17.374 −
0.35684
x
F
None of the above
Question number 11.
Your answer was D. Correct. Which of the following would be the LSRL for the given data?
x
1 7 7 12 13 20 y
44 37 27 21 22 14 A
B
C
D
E
None of the above
Question number 12.
Your answer was B. Correct. Suppose you have the following data:
x
1 2 3 4 5 6 y
44 37 29 21 25 14 and the LSRL is . Find the residual value for x
= 1.
A
42.187
B
1.813
C
D
-1.813
E
None of the above
Question number 13.
Your answer was B. Correct. In the least-squares regression line, the desired sum of the errors (residuals) should be
A
maximized
B
zero
C
1
D
positive
E
negative
Question number 14.
Your answer was D. Correct. The decline of salmon fisheries along the Columbia River in Oregon has caused great concern among commercial and recreational fishermen. The paper 'Feeding of Predaceous
Fishes on Out-Migrating Juvenile Salmonids in John Day Reservoir, Columbia River' (Trans. Amer. Fisheries Soc. (1991: 405-420) gave the accompanying data on y = maximum
size of salmonids consumed by a northern squaw fish (the most abundant salmonid predator) and x = squawfish length, both in mm. Here is the computer software printout of the
summary:
Coefficients: Estimate Std. Error t value Pr(> |t|) (Intercept)
−
91.030 16.713 −
5.447 0.000 Length
0.710 0.048 14.730 0.000 Using this information, give the equation of the least squares regression line.
A
ŷ
= 0.710
x
+ 16.713
B
ŷ
= −
91.030
x
+ 0.710
C
ŷ
= 16.713
x
+ 0.048
D
ŷ
= 0.710
x
−
91.030
E
ŷ
= 16.713
x
−
91.030
F
None of the above
= 43.54
x
−
1.604
y
^
=
−
43.54
x
−
1.604
y
^
= 1.604
x
+ 43.54
y
^
=
−
1.604
x
+ 43.54
y
^
=
−
5.543
x
+ 47.73
y
^
44
