Chapter 5 Discrete Probability Distributions
Learning Objectives 1. 2. 3. 4. 5. 6. Understand the concepts of a random variable and a probability distribution. Be able to distinguish between discrete and continuous random variables. Be able to comput
Regression Using BAII Plus Calculator
Y = a + bX
or
y = b0 + b1X
Assume this is the data set.
X
Y
1
3
2
7
3
5
4
11
5
14
2nd
Data (#7)
X01 = 1
Enter
Y01 = 3
Enter
X02 = 2
Enter
Y02 = 7
Enter
X03 = 3
Enter
Y03 = 5
Enter
X04 = 4
Enter
Y04 = 11
Enter
X05 = 5
Chapter 2 Descriptive Statistics: Tabular and Graphical Methods
Learning Objectives 1. 2. Learn how to construct and interpret summarization procedures for qualitative data such as : frequency and relative frequency distributions, bar graphs and pie
Chapter 1 Data and Statistics
Learning Objectives 1. 2. 3. 4. 5. 6. 7. 8. Obtain an appreciation for the breadth of statistical applications in business and economics. Understand the meaning of the terms elements, variables, and observations as they
Dr. Js note for 6-18-b
The shaded area in the left tail of the curve is the area that answers the question in 6-18-b.
The normal table in your book shows that the area to the left of Z = -1.22 is 0.1112.
So, the answer is that approximately 11.1% of the s
A multiple regression equation is:
Yhat = -1.2 + 1.3 X1 + 2.9 X2 + 8.8 X3
Where:
X1 is number of employees in thousands
X2 is number of stations in hundreds,
X3 is crude oil inventory in millions of dollars
Yhat estimates revenues in millions of dollars
E
Here is my explanation for all parts of problem 5-38.
a.
You must use equation 5.11.
The problem says to use mu=3.
So, plug 3 for mu in equation 5.11 to answer part a.
b.
Here: mu=3, x=2. To solve this with your calculator put in the following key-strokes
How Confidence Interval for Armand Problem was computed
When you make a prediction of Y with the regression equation, you are really reporting
what the average Y would be for a given value of X.
To be able to use the estimated Y value with any confidence
Problem 6-7 D in 5th edition of Anderson/Sweeney/Williams book.
Students often ask how do the authors know $13000 is the optimum bid?
You could do an analysis such as what follows.
Dr. J.
lower limit upper limit Bid
10000
15000 10100
10200
10300
10400
105
This area is 1 0.1314,
which is 0.8686.
Look it up in body of
table to find the Z.
6-14-d: If the area to the right of Z is 0.1314,
then the area to the left of it is 0.8686 (i.e., 1
0.1314 = 0.8686).
Look up in the body of the table for 0.8686.
Read lef
Here is the regression equation for Armand Pizza Parlor:
Y^ = 60 + 5X.
Plug 0 for X.
You would get Y^ = 60. Plot that point (which is the intercept point and goes on the Y axis).
See this point plotted in figure 12.4 (page 473).
Now pick another value for
Forecasting: Some Notes on Time Series
Perhaps one of the most important skills that a manager must be trained to have is
forecasting. This is because forecasting is so pervasive in everyday aspects of any
organization. The daily activities and decisions
1
Alpha value and Single-exponential smoothing
Single exponential smoothing is nothing more than a weighted average. The smoothing constant
acts as the weight and depending on what value you give it (between 0 and 1), you weigh the
time series values diff
Details and Error Analysis Window of DS Software
Every time you run analysis with the forecasting module of the DS software, the second
result window that it generates is the "Details and Error Analysis" window. That window
is generated regardless of what
Which of the 3 smoothing models should be used and how does one know
which to use other than the fact that the most accurate model must be
selected?
There is no cook-book formula to make that decision.
Remember that software and technology is used to make
1
Regression Analysis:
Some Points to Remember
In applying regression as a forecasting tool, one must be cautious on several grounds:
1. There may be a double jeopardy involved if the values of the independent variable
must be forecasted in order to perfo
POM/QM for Windows Tutorials and Help Menu
Perhaps your best bet to get started with using POM/QM for Windows software is to go through the
tutorial that is available for it: http:/wps.prenhall.com/bp_weiss_software_1/0,6750,91661-,00.html
Once you are i
t
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
Y
1.6
3.4
6.87
4
2.3
5.33
13.4
4.63
2
6.87
22.8
12
2.6
8
28.8
12.8
This time series has trend and multiplicative seasonality in it.
You can see the upward trend. Also, the effect of the seasons are growing over tim
6-20-c
In 5th edition of
Anderson/Sweeney/
Williams
Total is
80%
20%
0.3
0.5
Z axis
0
Z=0.84 (from table)
(see text below)
To answer 6-20-c, we must look in the entries within the table (within the table means the
probability values, not the z vlaues that
Real-world application of correlation/regression by a student in one of my online sections:
I wanted to share a real world use of statistics in business. At work my department was tasked to
develop software for our doctors to type their patient encounter
Calculating SSE, MSE, and Stanard Error of Estimate for Q 12-39.
SSR
miles
(X)
15
17
38
21
47
31
34
sum
mean
SUMMARY OUTPUT
SSE
SST
multiply
Col D
Predicted Y
Riders(Y) X - Xbar Y - Ybar Col D & E squared (Y hat)
(Yhat-Ybar)^2 (Y-Yhat)^2
(Y-Ybar)^2
-14 -2
A
B
C
D
E
F
G
H
capacity price
X - Xbar*
Y-hat
X
Y
X- Xbar Y - Ybar Y - Ybar (X- Xbar)^2 predicted
4
1595 0.7222222 360.55556 260.40123 0.52160494 1695.76829
4
1399 0.7222222 164.55556 118.84568 0.52160494 1695.76829
4
1890 0.7222222 655.55556 473.45679 0
Data
Using Qualitative Data as Independent Variable in Multiple Regression
Risk
Age
Pressure Smoker
Smoker
12
57
152
0
No
24
67
163
0
No
13
58
155
0
No
28
59
196
0
No
31
78
120
0
No
15
78
98
0
No
22
71
152
0
No
15
60
199
0
No
8
66
166
0
No
3
62
117
0
No
5
Data for problem 13-37 has been modified in this example
I have changed one variable in problem 37 to make it a 3-level qualitative variable.
Position is coded with two X variables: receiver & tackle.
Other independent variables used are: Weight and Speed
To understand Q32 in chapter 13, you must understand the example on page 560
Number 32 is "identical" to the text problem described on page 560. The difference is
that in 32 you are not given numbers; you are asked to develop the model in
mathematical abs