1. A small accounting firm pays each of its five clerks $35,000, two junior accountants $80,000 each, and the firm's owner $350,000. What is the mean salary paid at this firm? (Round your answer to the nearest whole number.) $   How many of the employees earn less than the mean?  employees What is the median salary? $  2. A small accounting firm pays each of its five clerks $35000, two junior accountants $90000 each, and the firm's owner $256000. What is the mean salary paid at this firm?   How many of the employees earn less than the mean?   What is the median salary?   If this firm gives no raises to the clerks and junior accountants, but the owner now has a salary of $435000. How does this change affect the mean? The mean increases by $  . How does it affect the median? The median increases by $  . 3. A study of diet and weight gain deliberately overfed 16 volunteers for eight weeks. The mean increase in fat was x = 2.63 kilograms and the standard deviation was s = 1.21 kilograms. What are x and s in pounds? (A kilogram is 2.2 pounds.) x =  s =  4.Every few years, the National Assessment of Educational Progress asks a national sample of eighth-graders to perform the same math tasks. The goal is to get an honest picture of progress in math. Suppose these are the last few national mean scores, on a scale of 0 to 500. Year 1990 1992 1996 2000 2003 2005 2008 Score 265 266 270 271 278 279 281 (a) Make a time plot of the mean scores, by hand. This is just a scatterplot of score against year. There is a slow linear increasing trend. (Do this on your own.) (b) Find the regression line of mean score on time step-by-step. First calculate the mean and standard deviation of each variable and their correlation (use a calculator with these functions). Then find the equation of the least-squares line from these. (Round your answers to two decimal places.)  =  +  x Draw the line on your scatterplot. What percent of the year-to-year variation in scores is explained by the linear trend? (Round your answer to one decimal place.)  % (c) Now use software or the regression function on your calculator to verify your regression line. (Do this on your own. 5. A student wonders if tall women tend to date taller men than do short women. She measures herself, her dormitory roommate, and the women in the adjoining rooms; then she measures the next man each woman dates. The data (heights in inches) are listed below. Women (x) 65 63 63 64 69 64 Men (y) 72 67 69 69 69 68 (a) Make a scatterplot of these data. (Do this on paper. Your instructor may ask you to turn this in.) Based on the scatterplot, do you expect the correlation to be positive or negative? Near ± 1 or not? The correlation should be positive. It should be near 1.The correlation should be negative. It should be near -1.    The correlation should be positive. It should not be near 1.The correlation should be negative. It should not be near -1. (b) Find the correlation r between the heigh ...

1. 1. A small accounting firm pays each of its five clerks $35,000,
two junior accountants $80,000 each, and the firm's
owner $350,000. What is the mean salary paid at this firm?
(Round your answer to the nearest whole number.)
$
How many of the employees earn less than the mean?
employees
What is the median salary?
$
2. A small accounting firm pays each of its five clerks $35000,
two junior accountants $90000 each, and the firm's
owner $256000.
What is the mean salary paid at this firm?
How many of the employees earn less than the mean?
What is the median salary?
If this firm gives no raises to the clerks and junior accountants,
but the owner now has a salary of $435000.
How does this change affect the mean?
The mean increases by $ .
How does it affect the median?
The median increases by $ .
3. A study of diet and weight gain deliberately overfed 16
volunteers for eight weeks. The mean increase in fat

2. was x = 2.63 kilograms and the standard deviation
was s = 1.21 kilograms. What are x and s in pounds? (A
kilogram is 2.2 pounds.)
x
=
s
=
4.Every few years, the National Assessment of Educational
Progress asks a national sample of eighth-graders to perform the
same math tasks. The goal is to get an honest picture of
progress in math. Suppose these are the last few national mean
scores, on a scale of 0 to 500.
Year
1990
1992
1996
2000
2003
2005
2008
Score
265
266
270
271
278
279
281
(a) Make a time plot of the mean scores, by hand. This is just a

3. scatterplot of score against year. There is a slow linear
increasing trend. (Do this on your own.)
(b) Find the regression line of mean score on time step-by-step.
First calculate the mean and standard deviation of each variable
and their correlation (use a calculator with these functions).
Then find the equation of the least-squares line from these.
(Round your answers to two decimal places.)
= + x
Draw the line on your scatterplot. What percent of the year-to-
year variation in scores is explained by the linear trend? (Round
your answer to one decimal place.)
%
(c) Now use software or the regression function on your
calculator to verify your regression line. (Do this on your own.
5. A student wonders if tall women tend to date taller men than
do short women. She measures herself, her dormitory roommate,
and the women in the adjoining rooms; then she measures the
next man each woman dates. The data (heights in inches) are
listed below.
Women (x)
65
63
63
64
69
64
Men (y)
72
67
69
69

4. 69
68
(a) Make a scatterplot of these data. (Do this on paper. Your
instructor may ask you to turn this in.) Based on the scatterplot,
do you expect the correlation to be positive or negative?
Near ± 1 or not?
The correlation should be positive. It should be near 1.The
correlation should be negative. It should be near -1. The
correlation should be positive. It should not be near 1.The
correlation should be negative. It should not be near -1.
(b) Find the correlation r between the heights of the men and
women. (Round your answer to three decimal places.)
(c) How would r change if all the men were 6 inches shorter
than the heights given in the table? Does the correlation tell us
whether women tend to date men taller than themselves?
r will not change. This correlation does imply that women tend
to date men taller than themselves.r will increase. This
correlation does not imply that women tend to date men taller
than themselves. r will not change. This correlation does not
imply that women tend to date men taller than themselves.r will
decrease. This correlation does imply that women tend to date
men taller than themselves.
(d) If heights were measured in centimeters rather than inches,
how would the correlation change? (There are 2.54 centimeters
in an inch.)
r will be multiplied by 2.54.r will not change. r will increase
by 2.54.r will be divided by 2.54.r will decrease by 2.54.
(e) If every woman dated a man exactly 3 inches taller than
herself, what would be the correlation between male and female
heights?

5. r will be equal to -1.r will be equal to 1. r will be the same as
the value in (b).r will be equal to 0.
6. timelength
10 3.3
20 .6
30 3.8
40 6.7
50 8.7
60 10.6
70 10.1
80 12.4
90 15.3
100 14.1
110 17.4
120 18.2
130 19.7
140 23.1
150 23.7
160 27.9
170 27.9
180 29.4
Find the mean and standard deviation of the times and icicle
lengths for the provided DATA above. Find the correlation
between the two variables. Use these five numbers to find the
equation of the regression line for predicting length from time.
Use the same five numbers to find the equation of the regression
line for predicting the time an icicle has been growing from its
length. (Round your answers to three decimal places.)
times x =
times s =
lengths x =

6. lengths s =
r =
time =
+ length
length =
+ time
7. Drilling down beneath a lake in Alaska yields chemical
evidence of past changes in climate. Biological silicon, left by
the skeletons of single-celled creatures called diatoms,
measures the abundance of life in the lake. A rather complex
variable based on the ratio of certain isotopes relative to ocean
water gives an indirect measure of moisture, mostly from snow.
As we drill down, we look farther into the past. Here are data
from 2300 to 12,000 years ago:
Isotope
(%)
Silicon
(mg/g)
Isotope
(%)
Silicon
(mg/g)
Isotope
(%)
Silicon
(mg/g)
−19.90
95

7. −20.71
154
−21.63
222
−19.84
104
−20.80
265
−21.63
237
−19.46
114
−20.86
271
−21.19
186
−20.20
139
−21.28
294
−19.37
333
(a) Make a scatterplot of silicon (response) against isotope
(explanatory).
Ignoring the outlier, describe the direction, form, and strength
of the relationship. The researchers say that this and
relationships among other variables they measured are evidence
for cyclic changes in climate that are linked to changes in the
sun's activity.
weak positive associationmoderate positive association strong
positive associationweak negative associationmoderate negative

8. associationstrong negative association
(b) Find the single outlier in the data. This point strongly
influences the correlation. What is the correlation with this
point? (Round your answer to two decimal places.)
What is the correlation without this point? (Round your answer
to two decimal places.)
(c) Is the outlier also strongly influential for the regression
line? Calculate the regression line with the outlier. (Round your
slope to two decimal places, round your y-intercept to one
decimal place.)
= − x
Calculate the regression line without the outlier. (Round your
slope to two decimal places, round your y-intercept to one
decimal place.)
= − x
Draw on your graph the two regression lines.
8. The table below gives data from a study that shows that
social exclusion causes "real pain." That is, activity in the area
of the brain that responds to physical pain goes up as distress
from social exclusion goes up. The scatterplot for this data
shows a moderately strong linear relationship. The data are
given below.
Social

9. Brain
Social
Brain
Subject
distress
activity
Subject
distress
activity
1
1.22
−0.055
8
2.20
0.029
2
1.83
−0.040
9
2.58

10. 0.031
3
1.08
−0.030
10
2.75
0.033
4
2.56
−0.015
11
2.75
0.064
5
2.17
−0.015
12
3.37
0.077
6
2.63
0.015

11. 13
3.65
0.124
7
2.01
0.021
(a) What is the equation of the least-squares regression line for
predicting brain activity from social distress score? (Round
your answers to four decimal places.)
brain activity
= social distress +
Make a scatterplot with this line drawn on it.
(b) On your plot, show the "up and over" lines that predict brain
activity for social distress score 2.7. Use the equation of the
regression line to get the predicted brain activity level. Verify
that it agrees with your plot. (Round your answer to four
decimal places.)
(c) What percent of the variation in brain activity among these
subjects is explained by the straight-line relationship with
social distress score? (Round your answer to a whole number.)
%