GM 533 Week 1 Lecture - Applied Managerial Statistics

1. Week 1 Lecture
GM 533
Applied Managerial Statistics
Professor Brent Heard
Not to be copied or linked to without
my permission

2. Week 1 Lecture GM 533
• Consider the following data on impulse items bought at the
checkout line of big box store and calculate the relative
frequency for each scenario. Explain what relative frequency
is and how you calculated it.
# of Impulse Items Purchased Frequency
0 Items 29
1 Item 7
2 Items 5
3 Items 4
4+ Items 2

3. Week 1 Lecture GM 533
• The following is a relative frequency distribution of lunch preference on an
Air Force base.
Lunch Preference Relative Frequency
Bring Lunch 0.27
Eat on base 0.37
Eat off base 0.31
Do not eat lunch 0.05
• If this was the distribution of 11,600 people on the Air Force base, find the
frequency for each lunch preference, explaining your calculation and then
noting what you would do with the information if you were considering
opening a restaurant just outside the Air Force base.

4. Week 1 Lecture GM 533
• A random sample of 10 engineers was asked how
much change in coins they had in their pockets
on a given day. The responses were:
0.78 0.58 0.75 2.30 0 1.23 1.45 0.75 1.80 0.77
• Find the mean, mode, median and midrange for
this set of data. You may have to look midrange
up, but it is also a measure of center. Compare
the four and note how they relate.

5. Week 1 Lecture GM 533
• In order to stay in the honors program, Mary
needs to have at least a 90 average in her
Geology class. She only has her final exam left
which counts for 30% of her grade. She has had 7
graded assignments throughout the term and
each of them counted 10% toward her final
grade. Her 7 graded assignment scores were:
78 89 97 92 84 94 88
• What does Mary need to make on her final exam
to have a 90 average?

6. Week 1 Lecture GM 533
• A company is tracking the amount of sick leave
employees use in a given year, they decided to
use the legal department’s 11 employees as a
sample. Their sick leave in hours/year for 2011
was the following:
32 40 0 16 48 12 14 24 26 30 38
• Note the mean, variance and standard deviation
for this set of data and explain how you might use
this information in planning, budgeting, etc.

7. Week 1 Lecture GM 533
• A company is tracking the amount of sick leave employees
use in a given year, they decided to use the legal
department’s 11 employees as a sample. Their sick leave in
hours/year for 2011 was the following:
32 40 0 16 48 12 14 24 26 30 38
• The company is considering giving bonuses to employees
who use 0 hours of sick leave (this may be illegal, this is
only an example from a math guy). Find the z score for 0
sick leave hours and explain what percentage of employees
would get a bonus based on this example. (We would have
to assume this data is normally distributed.)

8. Week 1 Lecture GM 533
• A company is tracking the amount of sick leave
employees use in a given year, they decided to
use the legal department’s 11 employees as a
sample. Their sick leave in hours/year for 2011
was the following:
32 40 0 16 48 12 14 24 26 30 38
• Calculate the first, second, third quartiles and
interquartile range. Explain what each means
and you might display the information in a
presentation.

9. Week 1 Lecture GM 533
• The following table shows the average
bonuses per employee for an accounting firm
from 2004 to 2011. Bonuses are given at the
end of the calendar year.

10. Week 1 Lecture GM 533
Year Avg. Bonus
2004 $2,500
2005 $2,800
2006 $3,000
2007 $3,400
2008 $3,200
2009 $2,000
2010 $1,000
2011 $1,100
Determine the percentage change in
the average bonuses from 2006 to 2010

11. Week 1 Lecture GM 533
• According to a recent survey of taxi cab drivers
in a major city, a driver spends an average of
8.7 hours a day in their cab. The standard
deviation was calculated to be .72 hours and
the distribution is approximately normal. Find
the three intervals noted in the Empirical Rule
and note what they are, how they are
calculated and what they mean.

12. Histograms with Minitab
• Open your Excel File, in my example, we will
use Case 27 (House Data)
• Select all headers and data by doing a click
drag (Left click top left corner, hold down drag
to bottom right corner)
• See following chart

13. Histograms with Minitab
• Just capture headers and all data…

14. Histograms with Minitab
• Right click or Copy what you have selected in
Excel
• Go to a blank Minitab Project Worksheet and
put your cursor in the top left blank gray cell
and paste
• See following chart

15. Histograms with Minitab
• Click here and paste

16. Histograms with Minitab
• You will now have something like this…

17. Histograms with Minitab
• Now in Minitab,
• At the top, Click Graph, Choose “Histogram”
• Click “OK” for Simple Histogram
• You should see this

18. Histograms with Minitab
• We are doing a histogram on Age of Homes,
so double click “C8 Age” and it will appear in
the Graph Variables box.

19. Histograms with Minitab
• I added a Title using the Label button, then I clicked “OK”
• Voila, you have it. Right Click, Copy Graph to put it
anywhere you wish

20. Week 1 Lecture GM 533
• In the next couple of days, I will post these
online at my “Statcave” site on Facebook.
• You DO NOT have to be a Facebook person to
see these, I simply post them there for
convenience.
• Website: www.facebook.com/statcave