Download QBA 260 -- Business Statistics

QBA 260 -- Business Statistics
Practice Exam #1
Time One Hour
This exam is open book and open notes. You are expected to use the computer to help
answer questions. The data set for the exam are in the Excel file listed under the Practice
Exam link at the course website. The data set consists of two columns. The first column
contains the square footage of an apartment unit and the second contains the monthly
rental for that unit.
1. (10 pts) Using the Sq. Footage in worksheet Data 1, do the following. Use the
Histogram option in Data Analysis Tools to create a graph with bins having upper limits
of 400, 800, 1200, 1600 and 2000. Copy the frequencies into the table below.
Upper
limit
400
800
1200
1600
2000
Above
2000
Frequency
2
12
69
17
0
0
2. (5 points) What are the upper and lower limits of the modal class? 801 – 1200
modal class = the class (category) having the greatest frequency
3. (5 points) Looking at the histogram, judge whether the data are (circle one)
nearly symmetric
strongly positively skewed
strongly negatively skewed
If you look at it rather than testing it, it looks almost symmetrical. However, if you run
the skew function on it, you will see that it is negatively skewed.
4. (9 points) Using the Monthly Rental data, compute the following statistics assuming
the data represent a population:
A. The average ____1236.51____________
B. The standard deviation_____433_________
C. The median_______1209___________
5. (8 points) If Monthly Rental follows a normal distribution with a mean of 1200 and
standard deviation of 500, the fraction of apartments with rents below 1000 would be:
.3446 or 34.46%
6. (8 points) If Monthly Rental follows a normal distribution with a mean of 1200 and
standard deviation of 500, 80% of the rent amounts will be above what amount?
Area from 0 to –Z = .3000 so –Z = -.85
-.85 = (X – 1200)/500
X = 775
Answer = $775
7. (15) points) Create a scatter plot with the Sq Footage on the horizontal axis and
Rental costs on the vertical axis. Add a linear trend line.
Impact of Square Footage on Rental Costs
2500
Rental Cost
2000
1500
1000
500
0
0
200
400
600
800
1000
Square Footage
1200
1400
1600
1800
y = 1.0942x + 148.58
What is the approximate value on the trend line when the apartment size is 1400 sq feet?
X = 1400
Y = (1.0942 * 1400) + 148.58
Y = 1680.46
Is the relation between rent and apartment size positive or negative?
Positive. As square footage goes up, rent goes up.
Multiple choice questions (4 pts each)
1. The average squared deviation is also known as
a. The absolute deviation
b. The variance
c. The standard deviation
d. The interquartile range
e. The range
2. When the formula = $A3 is copied to another cell
a. Both the row and column remain fixed
b. The column remains fixed
c. The row remains fixed
d. The value is unchanged
e. The format is change to “currency”
3. The sum of squared deviations about the median is
a. Less than the sum of squared deviations about the mean
b. Always zero
c. A measure of skewness
d. Not negative
e. Equal to the variance
4. Social security numbers are on which scale:
a. Nominal
b. Ordinal
c. Interval
d. Ratio
e. Diatonic
5. With data skewed to the right (positive skew)
a. The mean is smaller than the median
b. The median is smaller than the mean
c. The mean is smaller than the mode
d. The median is smaller than the mode
e. The mode is larger than either the mean or the median
6. The value that divides a dataset into an upper and lower half is called
a. the average
b. the mean
c. the median
d. the mode
e. the division
7. When data are standardized, the average value will be
a. zero
b. equal to the standard deviation
c. unchanged
d. measured in units of standard deviation
e. one
8. The function PERCENTRANK(A1:A100,20) will return
a. the rank of the value 20 among the 100 values in A1:A100
b. the fraction of values in A1:A100 that are less than 20
c. the fraction of values in A1:A100 that are more than 20
d. the number of values greater in A1:A100 that are less than 20
e. the average of the values in A1:A100 less than 20
9. Rejecting a true null hypothesis is known as
a. a type I error
b. a type II error
c. a standard error
d. a false positive
e. a false negative

10. Not rejecting a false null hypothesis is known as
a. a type I error
b. a type II error
c. a standard error
d. a false positive
e. a false negative
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