Fall Semester 2010
Wednesday Night
Instructor: Dr. Steven W. Lamb
Office Location: Room 921, School of Business
Telephone Number: 237-2114
Fax Number: (812) 237-8129
E-Mail address: steven.lamb@indstate.edu
Office Hours :
MWF 2:00-3:30
Please feel free to call. If I am not in, leave a voice-mail message on my phone, and I will get back to you.
I can easily help you over the phone on any specific quantitative procedure that we are covering in class.
Catalog Description and Prerequisites
This course refines the decision-makers skills, utilizing quantitative tools to provide better information upon which to base a decision. Students will learn a structured approach to problem solving that focuses on selecting appropriate modeling techniques for a variety of decision challenges that may face a general manager. Particular attention will be given to the difficulty that managers face when making decisions about an uncertain future.
Required Textbook :
th
Optional Materials:
A handheld calculation is of value in the classroom, and access to a computer using the Windows
Environment with Microsoft Excel is of value.
Course Educational Objectives:
At the end of the course, students should understand
the concept of structured problem solving
the role of model building in developing good decisions
the role of uncertainty in decision making
the necessity of coordinating data collection techniques with the choice of a data analysis tool
the role of statistics in achieving and maintaining the quality of the firm’s products and processes
the role of statistics in exploring the defining data relationships for improved managerial decision making
the role of forecasting in planning
Perspective Coverage
Ethical issues
Students will learn how to interpret information accurately, without bias. They will learn how to gather information from the data, rather than how to use the data to reach pre-designed conclusions. They will be exposed to many of the pitfalls of data presentation.
Political, social, legal and regulation, environmental and technological issues
Given the advancement of technology, data can be analyzed indefinitely by numerous techniques.
The student is instructed as to how to develop and test a model rather than to select that model among many models which supports the original bias. Methods of demonstrating associations between political philosophy and social attitudes are presented.
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Demographic diversity
The tools presented allow the student to better understand and present data sets. The student is
better equipped to adsorb state, national, and international diversity trends, rather than continue to assume that the demographic realities present in their immediate environment reflect broad patterns.
Communication Coverage
Students will have opportunities to discuss appropriate quantitative methods to address business problems.
Evaluation
There will be two equally weighted major exams during the course of this semester. I will ask you to bring to this exam: your class notes; any additional notes you have constructed, such as a couple of pages devoted to formulas; example problems; and the completed problem assignments, the Excel output associated with the problem assignments; SPSS output that I have assigned you to accomplish or SPSS output given to you in class. I would appreciate this material being placed in a three-ring notebook in a highly organized framework. During the course of the test, you will be asked to refer to this material for quantitative and/or qualitative purposes and interpretation. You may also be asked to hand in specific problems or computer output from your homework after you have completed your test. You may also be asked to hand in specific problems and/or computer output from your homework at various times during the span of the semester.
You will also have a paper to complete that in some fashion or another utilizes some of the quantitative techniques that you are exposed to in the classroom.
The Coupling of Excel, & SPSS with Statistical Procedures
Before proceeding to more advanced quantitative procedures, this course will begin with a quick review of the materials covered in a basic statistics course. The textbook that we are using “ Statistics for Business and Economics ” may be used for an excellent review of basic concepts and that review may be accompanied with some exposure to Microsoft Excel . SPSS will be introduced by the instructor.
Sequencing of Materials
The topics in a basic statistics course that you need to master are given below along with the pages in our text book in which they are found. Some of the topics found in a basic statistics course I will briefly review
(those that have this symbol **) and will then assume that they are at your disposal.
Those topics are found on the following pages in
I will only review those that have the double star.
Topic Chapter(s) pages
Rules of Summation & Double Summation Notation ** Appendix C 946-947
Data Sources, & Organizing Data 1,2 1-70
Summarizing and Describing Data 3 82-137
Measures of Central Tendency, ** 3 83-87
Variation and Shape 3 98-102
Population Measures
Mean ** 3 84
Variance, Standard Deviation ** 3 93
Basic Probability 4 141-177
You should have all this material in this chapter in your memory
Discrete Probability Distributions 5
Prob. Distribution for Discrete
Random Variables 5 190-193
Mean, Standard deviation & Variance of a
Discrete Random Variable ** 5 196-197
Binomial Distribution** 5 200-208
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I will briefly review all of the following items. You would have had exposure to these items in your undergraduate experience.
Topic Chapter pages
The Continuous Distributions instructor ,6 227-231
Normal Distribution 6 231-241
Normal Approximation to the Binomial 6 243-245
Sampling Distribution of the Mean 7 267-277
CI for the mean (Sigma Known) 8 301-305
CI for the mean (Sigma unknown) 8 307-313
Sampling Distribution of the Proportion 7 280-282
CI for the Proportion 8 319-320
Sample Size Determination for the Mean and Proportion 8 316-321
Hypothesis Testing
The Hypothesis Testing Procedure; Type I and II Errors 9 340-342
Test of Hypothesis for Mean; (Sigma Known), 1 & 2 tail 9 345-354
The P-Value Approach 9 347-349
Tests of Hypothesis for the Mean, (Sigma Unknown) 9 359-361
Inferences about the diff. between 2 indep means,
Variances known, then unknown 10 395-406
Topic Chapter p ages
Selected usage’s of the Chi-Square Distribution
Theory of Chi-Square Distribution 11, Instructor 435-438
Confidence interval for Variance (2 tailed) 11 435-440
Confidence interval for Variance (1 tailed) Instructor
Goodness of Fit test & Test for Independence 12 459-479
Introduction to the F Distribution
Theory of F Distribution Instructor
F test for Differences in two Variances 11 445 -450
One Way ANOVA Completely Randomized Design- Fixed Effects Model
Assumptions, Model and Rational Instructor
Calculations 13 492-512
Post-Hoc Tests (Fisher’s LSD) 13 508-512
Other Multiple Comparison Procedures Instructor
Randomixed Block Design 13 514-517
Assumptions, Model, and Rational Instructor
Multiple Comparison Procedures Instructor
Two-way Anova with Interaction 13 521-526
Assumptions, Model and Rational Instructor
Multiple Comparison Procedures
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Simple Linear Regression and Correlation 11
Extensive coverage of Multiple Regression Topics chosen from chapter 12
Students will become acquainted with SPSS output. They will also be asked to read and master articles written by the instructor concerned with the application of applied multiple regression procedures to the analyses of compression inequities in faculty salaries.
Time Series Forecasting Topics chosen from chapter 13
Forecasting techniques will include the use of
1. moving averages,
2. weighted moving averages including sum of years digits
3. exponential smoothing techniques
4. double exponential smoothing
4. Simple linear regression with coding
5. Quadratic equation using coding
6. Logarithmic exponential model
Y = ab x
.
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