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The Fletcher School
The Graduate School of International Relations
EIB B206: Data analysis and Statistical Methods for Business
Dr. Robert A. Nakosteen
Email address: [email protected]
Telephone: (413) 545-5687 Fax: (413) 545-3858
Office hours: Tuesday and Thursday before class.
Text: Levine, et al, Statistics for Managers Using Microsoft Excel, 5th edition, Prentice
Hall, 2008 ISBN-10: 0132252147
Note: The text is an “out of edition” text, as there is a 6th edition available. The only
substantive difference between the 5th and 6th editions is their cost.
I have not ordered the text from the campus book store. You can purchase these texts less
expensively online, or from a student who has taken this course. Students who have
taken this course previously may try to sell you the 4th edition of the text which I no
longer support.
For a full version of the syllabus go to https://trunk.tufts.edu
This course provides an overview of classical statistical analysis and inference. The goal
is to provide you with an introduction to statistical thinking, concepts, methods, and
vocabulary. This will give you some tools for dealing with statistical methods you may
encounter in future course work, and in the business world. A number of topics address
specific business applications, including economic forecasting and statistical quality
control.
Due to the compressed timeframe for the course, things will go very quickly. Please work
to be sure you do not fall behind. Let me know right away if you begin to encounter
problems.
We will make some use of spreadsheet technology in this course, especially in the course
section on regression analysis. It will be a useful tool for some of your homework. Any
work you can do to review spreadsheet technology would be helpful. The spreadsheet of
preference in this course will be Microsoft Excel. Knowledge of Excel is not, however, a
requirement for this course.
I will be commuting from Amherst for this course, and will not be on campus at other
times. This presents us with a challenge when you want to talk about course material in
the interval between classes. I am available at virtually all times on my email account:
[email protected].
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Feel free to email me directly with any questions or problems. By the way, the email
address listed for me in the Fletcher School faculty directory is programmed to forward
email immediately to me.
Grades: Your grade will be determined by your performance on the two examinations.
Each exam will be of approximately the same weight. The examination schedule can be
viewed in the course outline.
The grading scale for the course follows:
97-100: A
93-96: A89-92: B+
85-88: B
81-84: BHomework: A large number of “homework” problems are assigned. This is probably the
most important way in which you will learn statistical concepts, by working out answers
to assigned problems. Homework will not be graded. Your incentive to do the homework
is both esoteric (to learn) and practical (practice for exams). Answers to most questions
are in the text. There is also a solutions manual for both text editions on Blackboard, for
most chapters we cover. This manual provides more detailed answers than does the text.
The assignment for chapter 3 will be collected and checked.
I will always spend as much time as needed going over problems in class. The
examinations, while not taken directly from homework problems, are consistent with the
problems I assign. This is a good, “anxiety free” way to study for examinations.
Students with Disabilities: “In accordance with federal and state law, Tufts University
provides for reasonable accommodations to students with documented learning
disabilities. If you believe you have a disability requiring accommodation, please contact
Nora Moser McMillan, Registrar and Manager of Student Academic Programs, Goddard
212, (617) 627-2405.”
Excel: The knowledge of Excel spreadsheets is not a requirement of this course.
However, you can use this opportunity to learn and/or enhance your knowledge of this
valuable tool. It is especially useful for the final topics in the course. The downside of
using an out-of-edition text is that the Excel appendixes are out of date.
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Course outline: (note: It is a rare academic term where I follow my own schedule. Stay
tuned.):
Week 1: Introduction: Basic statistics and concepts; the nature of numerical
information; sampling methods; presenting numerical information; descriptive measures
of central tendency, dispersion, skew, and kurtosis. Chapter 1; Chapter 2; Chapter 3
(skip section 3.4); and Chapter 7 (sections 7.1 and 7.2 only). The concepts and rules of
probability. Chapter 4. Note: this subject may carry over into the next week.
Weeks 2: Complete probability concepts and rules. Discrete probability distributions:
The expected value operator; covariance and its application to finance; the binomial
distribution. Chapter 5 (read sections 5.1, 5.2, and 5.3 only).
The normal distribution and sampling distributions. Chapter 6 (skip sections 6.3, 6.4, 6.5,
and 6.6; read “Excel Companion to Chapter 6”), and chapter 7 (skip sections 1 and 2,
which you have read earlier).
Week 3: Complete normal distributions and sampling distributions. Statistical inference
I: Confidence intervals. Chapter 8 (skip section 8.5; and all material about “proportions”).
Week 3: First Examination.
Week 4: Statistical inference II: Hypothesis testing. Chapter 9 (skip all material about
“proportions”) and chapter 12 (sections 12.1 and 12.3 only).
Weeks 4 and 5: Statistical inference III: Correlation and regression Analysis. Chapters
13 (skip section 13.6, and 13.8; read “Excel Companion to Chapter 13”) and 14 (sections
14.1, 14.2, 14.3, and 14.4 only).
Week 6: Economic forecasting: Chapter 16 (sections 3 and 4 only).
Week 6: Statistical quality control; the statistics of control charts: Chapter 18 (sections 3,
4, and 6 only).
Note: The second exam is a “take-home” exam, and will be distributed on the final day
of class. This is not a comprehensive final exam, but rather will be solely focused upon
material since the first exam.
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ASSIGNED PROBLEMS
I will not go over homework unless prompted to do so. I will answer any and all
questions regarding to homework, including working out the problems in detail.
However, you should attempt all problems on your own. All of the assigned problems are
answered, too briefly, at the back of your textbook. In addition to these abbreviated
answers, I have linked more detailed answers from the text’s instructor’s manual to
https://trunk.tufts.edu
Once you are into the site for this course, go to the course documents option. There you
will find separate files with answers to all of the chapter problems, even those I have not
assigned.
There are multiple parts to most questions. Please complete all parts of each question
assigned, unless specifically excluded.
Chapter 1: Problem 1.16; Chapter 7: Problems 7.7, 7.12.
Chapter 2: There are no assigned problems from this chapter. Please read the chapter
with a focus on becoming familiar with the ways numerical data can be displayed.
Chapter 3: Problems 3.4, 3.22, and 3.40 (this assignment will be collected).
Chapter 4: Problems 4.4, 4.8, 4.14, 4.16, 4.22, 4.26, and 4.32 (this is a Bayes problem,
and is completely optional).
Chapter 5: Problems 5.2, 5.8, 5.18, 5.21, 5.28.
Chapter 6: Problems 6.1, 6.2, 6.4, 6.6, 6.8, and 6.12.
Chapter 7: Problems 7.18, 7.22, 7.28, 7.30.
Chapter 8: Problems 8.2, 8.4, 8.8, 8.12, and 8.38.
Chapter 9: Problems 9.9, 9.10, 9.13, 9.28 (in answering this question, please state the
null and alternative hypothesis), 9.44 (in answering this question, please state the null and
alternative hypothesis), and 9.60 (parts a. and b. only)
Chapter 12: Problems 12.2, 12.4, 12.8.
Chapter 13: Problems 13.1, 13.6, 13.18, 13.44 (part a. only). If you cannot complete
these problems using Excel, do not worry. I will not count this against you in assessing
your homework, and I will cover the material in class.
Chapter 14: Problems 14.1, 14.23.
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Chapter 16: Problems to be assigned.
Chapter 18: Problems to be assigned.
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