MBA535 (Analytical Tools for Decision-Making)
Week 2 Assessment (20 points each question; 100 points total)
Question 1. The data below represent the amount of grams of carbohydrates in a serving of breakfast
cereal in a sample of 11 different servings.
11
Percentages of row
Percentages of column
1200.0%
1200.0%
1000.0%
1000.0%
ND
OD
HD
800.0%
600.0%
NS
OS
HS
800.0%
600.0%
400.0%
400.0%
200.0%
200.0%
0.0%
0.0%
NS
OS
HS
ND
OD
HD
Chapter 1
In some sense this is where the course really begins. From this point on, please
read the material carefully, work through the examples and do the problems carefully.
For most sections listed in the Syllabus, in the notes, there will be a Previe
Lets Get Started
Why statistics?
The sections in this pre-chapter provide a quick discussion of what statistics is
about. Basically, there are two main things that you can do with statistics:
You can use statistics to summarize large or complicated data
Chapter 3
Chapter 2 focused on obtaining an overview of the data by displaying it in useful
formats. This chapter is about summarizing the data by computing a few useful numbers.
These numbers are often defined by complicated mathematical formulas that ar
Chapter 2
This chapter presents some simple techniques for organizing and displaying data,
either as numbers arranged on the page or as charts and diagrams. Most of these are fairly
self-explanatory.
This is also an opportunity to learn or practice some b
Chapter 9 Notes
(Sections 9.1 and 9.2)
Chapter 9 Overview
Suppose that an automobile manufacturer claims his vehicles average 30 miles
per gallon. If you randomly select one of these vehicles and you find that it gets 29 miles
to the gallon, you have some
Chapter 8 Notes
Chapter 8 Preview
This chapter continues to develop the idea of using the statistics computed from a small
random sample to estimate the corresponding parameters for the entire population. In
particular, it shows how to construct a small i
Chapter 5
Section 5.1: The Probability Distribution For a Discrete Random Variable
Variables A variable is a well-defined quantity that takes on different values depending
on the circumstances. For example, the variable T might represent the temperature i
Chapter 7
Chapter Overview: Some Comments on Random Sampling
Inferential Statistics deals with drawing conclusions. The theory behind most of
the techniques in this area is based on the assumption that the sample is drawn in a truly
random manner. There i
Chapter 6
Chapter Overview
This chapter introduces the concept of continuous random variables, and shows
various calculations with the three most important examples: normal random variables,
uniform random variables and exponential random variables.
Chapt
Chapter 4
Chapter 4 Preview
In chapters 4, 5 and 6, the authors lay out the mathematical theory of probability as
compactly as they can. Probability is the theoretical basis of inferential statistics. You
are certainly not expected to become a mathematica
MBA535 (Analytical Tools for Decision-Making)
Marist College
Week 1 Assessment (20 points each question; 80 points total)
Question 1. A sample of 200 students at a Big-Ten university was taken after the midterm to ask
them whether they went bar hopping th
A
Player
Vijay Singh
3 Tiger Woods
4 Phil Mickelson
5 Sergio Garcia
6 Kenny Perry
7 Anthony Kim
8 Camilo Villegas
9 Padraig Harrington
10 Stewart Cink
11 Justin Leonard
1
2
B
C
Age Events
45
23
32
6
37
21
28
19
47
26
22
22
26
22
36
15
35
23
35
25
D
Rounds
Y
Z
AA
AB
AC
AD
1
Lookup table for industry medians in
2008
2 Industry
3 Aerospace & Defense
4 Banking
5 Business Services & Supplies
6 Capital Goods
7 Chemicals
8 Conglomerates
9 Construction
10 Consumer Durables
Total compensation
14.29
2.29
2.47
9.00
4
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
A
Acme marketing decisions
B
C
D
E
F
G
H
I
J
K
L
M
Inputs
Fixed costs ($1000s)
Test market
National market
Unit margin
100
7000
$18
Possible quantities sold (1000s of units) in national market
A
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
B
C
D
E
Illustration of Bayes' rule using drug example
Prior probabilities of drug user status
User Non-user
0.05
0.95
1
Likelihoods of test results, given drug user status
User Non-user
Test positiv
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
A
Drug testing decision
B
C
Benefits
Identifying user
D
F
Given probabilities
25
Prior probabilities
User
0.05
Costs
Test cost
Barring non-user
Not identifying user
Violation of privacy
E
1
50
20
2
Non
A
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
B
C
D
E
F
G
SciTools Bidding Example
Inputs
Cost to prepare a bid
Cost to supply instruments
$5,000
$95,000
Probability of no competing bid
Comp bid distribution (if
1
2
3
4
5
6
7
8
9
10
11
12
A
SciTools Bidding Decision
B
C
Inputs
Cost to prepare a bid
Cost to supply instruments
Probability of no competing bid
Comp bid distribution (if they bid)
<$115K
$115K to $120K
$120K to $125K
>$125K
$5,000
$95,000
D
Range names
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
A
B
C
D
Calculating covariance and correlation between two random variables
Economic outcome
Depression
Recession
Normal
Boom
Means
Variances
Stdevs
Covariance
Correlation
Probability
0.05
0.30
0.50
0.15
GM Return
-20%
1
2
3
4
5
6
7
8
9
10
11
12
13
A
B
C
Mean, variance, and standard deviation of the market return
Economic outcome
Rapid Expansion
Moderate Expansion
No Growth
Moderate Contraction
Serious Contraction
Summary measures of return
Mean
Variance
Stdev
Probabili
A
1
2
3
4
5
6
7
8
B
C
D
E
F
Assessed probability distribution of sales of two popular PDAs
Daily sales of
Palm M505
0
1
2
3
0
0.01
0.02
0.03
0.04
Daily sales of Palm Vx
1
2
0.03
0.06
0.06
0.12
0.12
0.06
0.09
0.06
3
0.09
0.09
0.09
0.03
A
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
B
C
D
E
F
G
H
Covariances between stock returns (variances of stock returns are on the diagonal)
Stock1
Stock2
Stock3
Stock4
Stock5
Stock6
Stock7
Stock1
0.0154
0.0047
0.0061
0.0107
0.0157
0.0120
0.0077
Stock2
Conditional mean and variance formulas
Economy in coming year
State
Probability
Awful
0.2
Stable
0.5
Great
0.3
Conditional means, standard deviations, and variances of stock price change, given economy
State
Mean
Stdev Variance
Awful
-20%
30%
0.09
Stable