General Business 304 – Intermediate Business Statistics, Lectures 1 & 2 - Spring 2011
Instructor: Tim Welnetz
Lecture 1: Mondays and Wednesdays from 1:00 to 2:15pm in 1295 Grainger
Lecture 2: Tuesdays and Thursdays from 9:30 to 10:45am in 1295 Grainger
Office: Room 4279 Grainger
E-mail: twelnetz@wisc.edu
Phone: (608)262-8934 ext. 1
Website: http://courses.bus.wisc.edu
Office Hours: Mondays and Wednesdays 10:00 to 10:45am and 2:30 to 3:30pm; Tuesdays and
Thursdays 11:00 to 11:45am; and by appointment
Discussion/Tutor Lab: Tuesdays, Wednesdays, and Thursdays 4:35 to 5:25pm in 2294
Teaching Assistant: Xiaoli Jin
TA E-mail: xjin22@wisc.edu
Course Description
This course provides an overview of techniques for data analysis, including multiple regression, sampling
theory, and applications of probabilistic inference from sample data. The emphasis is upon the
applications of these techniques to management problems. Students are required to analyze data sets,
present their analyses in written form, and defend their conclusions. You will have opportunities to work
on your assignments using statistical software (most likely MS Excel) during the discussions on Tuesdays,
Wednesdays, and Thursdays from 4:35-5:25pm in room 2294 (a computer lab).
The course is designed to familiarize you with fundamental techniques for summarizing and analyzing
data found in the business environment and several other disciplines. It focuses on practical, hands-on
experience using data to study time trends, prepare models of business and economic phenomena, and to
discover important messages that may be found in an appropriate analysis of data. The course focuses
heavily on interpretation and communication of statistical results.
The course will familiarize you with statistical techniques that are widely found in the workplace. These
include graphical displays of data, time-series methods including statistical process control, understanding
relationships between variables, simple and multiple regression analyses, survey design, dealing with
missing or bad data, and forecasting. Regression analysis will be the statistical technique emphasized the
most and will take up more than half of the semester.
Handbook
Course Materials
Data Analysis Handbook, by Marlene A. Smith. This is your textbook. It is available at
the Copy Center in Grainger Hall for $17-$20. Bring it to every class, as I will often
show overhead transparencies of main ideas, data, tables, and graphs from this book.
Software
Any statistical software capable of handling the analyses needed for the assignments
will be fine, but I emphasize the use of Microsoft Excel 2007 and a little MINITAB in
lectures and in the computer lab.
Calculator
Please bring a calculator with you to each class. Your calculator should be able to
compute logarithms and raise numbers to a power. If you’re in the market for a good
statistical calculator, I recommend the TI-83+ (cost is about $100 or less when on sale).
Course Grade
Your course grade will be determined out of a total of approximately 500 points.
Three tests worth 100 points each and 7-8 assignments worth 25 points each. Out of
the total points in the course, students will be ranked and the top 20% will receive As,
the next 25% will receive ABs, likely the next 45-50% will receive Bs, and the last 5-
10% will likely receive BCs and lower. For the Bs and lower grades, the expected
grade scale is based on getting at least 81% of the course points for a B, 77% for a
BC, 70% for a C, and 60% for a D.
Course Etiquette Please turn off cell phones, IPods, and other electronic devices; however, I will allow
laptops only to be used for note-taking and participating in analyses I cover in class
(that means no e-mail, Facebook, or any other web-surfing); do not read
newspapers or magazines or have conversations during class; cheating is not allowed;
do not come to class late; participation is expected, and more than two unexcused
absences may result in a deduction of your grade or termination from the course.
The three tests will test you on course concepts through multiple choice questions in which you will mark
answers on a scantron. You will be allowed to use one side of one 8.5 by 11 inch sheet of notes for each
test. The three test dates are: Wed/Thurs Feb. 16/17, Wed/Thurs Mar. 30/31, and Sun. May 8. The first
two tests will be held in our regular classroom; the third, noncumulative “final” test will be 7:30-9:00pm
in a room to be announced later. Note: an optional make-up test will be given the last day of class
(Wed/Thurs May 4/5) during class time.
Each of the 7-8 assignments will consist of a data analysis problem on real-world data that I will provide
on the course web site. In addition to using statistical software to do the analyses for the assignments, you
may be required to also solve parts of them by hand (with a hand-calculator). You will also need to
provide brief comments/interpretations for each part of an assignment. Details on each assignment will be
provided on the course web site and due dates will be announced in lecture and on the “Assignments”
page of the course web site. Assignments will be graded on neatness, accuracy of analyses, and quality
and appropriateness of comments/interpretations. Read the “General Assignment Directions” (top of the
“Assignments” page) for more detail. No extra credit assignments will be offered.
We will cover the course in the order of the topics shown in the text. The main topics covered are listed
below along with the approximate length of time covered in class:
Data
Rounding
Graphs and Tables
Means, Medians, and Modes
Standard Deviations and Ranges
Runs Test
Normal Distributions
Control Charts
Smoothing Data
Correlation
Statistical Models
Least Squares
Simple Regression
Multiple Regression
Variable Selection
Categorical Predictor Variables
Residual Analysis
less than ½ a lecture
less than ½ a lecture
1 lecture
1 lecture
less than 1 lecture
1 lecture
less than 1 lecture
1 lecture
1 lecture
less than 1 lecture
less than ½ a lecture
1 lecture
2-3 lectures
1-2 lectures
2 lectures
2 lectures
1 lecture
In addition to the amount of time spent on the topics above, we will spend time in class doing activities that
emphasize application of some of the above topics.