In questions # 1 – 4, classify the
data generated for each question as Nominal, Ordinal, Discrete or
Continuous.
1.
) What is your age in years?
________________
2. )
Are you the person who typically shops for your household? __________
3. ) The
loss (in dollars) incurred by a store as a result of shoplifting. __________
4. ) The
final ranking of the 10 football teams in the Southeastern Conference at the
end of the season ___________
5. – 11. ) Fill in the missing
cells in the chart below.
|
Class Intervals |
Relative Frequency |
Frequency |
Cumulative Frequency |
|
10 |
|
20 |
20 |
|
20 |
0.15 |
|
|
|
30 |
0.05 |
10 |
60 |
|
40 |
|
|
|
|
50 |
0.25 |
|
200 |
12. ) Use
the following data set to construct a stem and leaf plot.
Data
Set : 51, 50, 47, 50, 48, 41, 59, 68,
45, 37
Use the sample data below to answer
questions # 13 - 17. Give the
numeric value and notation for the answer if there is one.
Data Set : 51, 50, 47, 50, 48, 41, 59,
68, 45, 37
13. ) Find the mean of the data set.
14. ) Find
the variance of the data set.
15. ) Find
the median of the data set.
16. ) Find
the first quartile of the data set.
17. ) Find
the 85th percentile of the data set.
18.
) An exam has a mean of 74 and a
standard deviation of 8. If a person’s standard score
on the test is –0.75, what was the person’s exam score ?
19. ) A
sample has a mean of 50 and a standard deviation of 4. Find the z-score for the x value = 59.
20.
) If you assume nothing about the
shape of the distribution, at most what percentage of a distribution will be
three or more standard deviations from the mean ?
21.
) Using the empirical rule, determine
the approximate percentage of a normal ( Bell-Shaped ) distribution that is expected to fall
between one standard deviation below the mean and two standard deviations above
the mean.
Use the following table to answer
questions # 22 - 25. The table shows x
= the number of hours a runner has ran during each of eight weeks and y
= the corresponding times in which she ran a mile at the end of the week:
|
Number of Hours Ran |
Times of Miles (Minutes) |
|
13 |
5.2 |
|
15 |
5.1 |
|
18 |
4.9 |
|
20 |
4.6 |
|
19 |
4.7 |
|
17 |
4.8 |
|
21 |
4.6 |
|
16 |
4.9 |
22. ) Find
the linear correlation between the number of hours run and the mile time and
explain what that value means.
23. ) Find
the equation of the least-squares regression line which will allow us to
predict the runner's time for the mile from the number of hours she ran that
week.
24. ) Predict
how fast the runner will run a mile at the end of a week in which she ran for
18.2 hours.
25. ) Predict
how fast the runner will run a mile at the end of a week in which she ran for
13.5 hours.