Business Analytics DT Review Practice Test.
The following data set lists the prices for thirty houses in and around Boston, Massachusetts. Create a histogram of the data using the bins provided in column D. - CORRECT ANSWER The Input Range is B1:B31 and the Bin Range is D1:D8. You must check t...
The following data set lists the prices for thirty houses in and around Boston, Massachusetts. Create a
histogram of the data using the bins provided in column D. - CORRECT ANSWER The Input Range is
B1:B31 and the Bin Range is D1:D8. You must check the Labels in first row box since we included B1 and
D1 to ensure that the histogram's axes are appropriately labeled.
How would you describe the shape of the distribution shown below of the real estate pricing data? -
CORRECT ANSWER Right-tailed
The following data set contains the heights of several members of the Boston Red Sox. Create a
histogram of the data using the bins provided in column C. - CORRECT ANSWER The Input Range is
B1:B11 and the Bin Range is C1:C4. You must check the Labels in first row box since we included B1 and
C1 to ensure that the histogram's axes are appropriately labeled.
How many houses cost more than $400 thousand and less than or equal to $800 thousand? - CORRECT
ANSWER Approximately 11
Below are three histograms showing the heights of several members of the Boston Red Sox. Which do
you think is more effective in showing the distribution of player heights? - CORRECT ANSWER Option B
This histogram effectively shows the overall distribution of player heights. The size of each bin is neither
too large nor too small to give an accurate representation of this sample of Boston Red Sox players'
heights.
To find MEAN: - CORRECT ANSWER =Average(range)
To find MEDIAN: - CORRECT ANSWER =Median(range)
To find MODE: - CORRECT ANSWER =Mode(range)
, Calculate the average weight of the infielders on the 2013 Red Sox roster. - CORRECT ANSWER The
average weight of the infielders is AVERAGEIF(B2:B11,"Infielder",C2:C11), or equivalently,
AVERAGEIF(B2:B11,E2,C2:C11)=198.0 pounds.
Calculate the 33rd percentile for the oil consumption data. - CORRECT ANSWER
PERCENTILE.INC(A2:A11,0.33)=2.79.
33%, or approximately one-third, of the countries in our data set consume less than 2.79 million barrels
of oil per day. 66%, or approximately two-thirds, of the countries in our data set consume more than
this amount.
Calculate the variance of the sample of Boston real estate pricing data. - CORRECT ANSWER The variance
is VAR.S(B2:B31)= 82,917,725,621 squared dollars.
Use the descriptive statistics tool to calculate the summary statistics for the data set provided below.
Use C1 as the output range so that your response is graded correctly and include a label for the data. -
CORRECT ANSWER The Input Range is A1:A13. You must check the Labels in first row box since we
included a label in cell A1 to ensure that the output table is appropriately labeled, and you must select
Summary Statistics to produce the output table.
You need to use C1 as your output range so that your calculations are in the blue cells for grading.
Suppose we wanted to compare the variability of the selling prices of Boston real estate to the
variability of Boston real estate lot sizes. Calculate the coefficient of variation of the selling prices. -
CORRECT ANSWER The coefficient of variation is STDEV.S(B2:B31)/AVERAGE(B2:B31)= 0.63.
Below are data showing students' grades on a statistics quiz and the number of hours they spent
studying. Create a scatterplot to show the relationship. - CORRECT ANSWER The Input Y Range is B1:B25
and the Input X Range is A1:A25. You must check the Labels in first row box since we included labels in
cell A1 and B1 to ensure that the scatter plot's axes are appropriately labeled.
What is the correlation between hours studying and quiz grades? - CORRECT ANSWER The correlation
coefficient of hours studying and quiz grades is CORREL(A2:A25,B2:B25)=0.67.
Note that the fact that the correlation is a positive number is reinforced by viewing the scatterplot of the
data; there appears to be a positive trend in the data.
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