Business Statistics introduces statistical methods used in economics and business. It is not a continuation of econ 155 (Mathematical Methods), but instead a course on statistics, probability, estimation, empirical studies, and related issues. The class will emphasize quantitative reasoning over proofs and mathematical formalism. We will work extensively with numbers (bring a calculator to class) and we will use Microsoft Excel for some assignments. A good understanding of statistical analysis is crucial to understand how the world works.
I. Summary Statistics
Descriptive statistics are the most familiar part of statistical analysis. Averages-- mean, median, mode-- sometimes called measures of central tendency; percentages; and measures of spread or dispersion -- variance, standard deviation-- are very common. We won't belabor these because most students have had some exposure to them. For an explanation of the basics, see Statistics Every Writer Should Know.
While calculations for Samples and Populations look similar, it's important to remember that a sample is only an estimate and we'll need to use probability theory to relate it to the true population parameter.
Graphs are often a useful supplement to descriptive statistics.
We can also look at relations between variables, using tools like correlation, covariance, and regression
II. Collecting Data
Whenever you read a statistic, a question should pop into
your mind, "where did this number come from?" Not all
numbers are created equally, even if they are printed on really nice glossy
paper. Methodology and definition are truly important.
Samples need to be random. Getting a true random sample requires real effort. Try these online sources of random numbers or these random numbers.
Lots of good data is available online. See Finding Data on the Internet for links to some sources.
Online data collection still has many issues to resolve.
III. Uncertainty, Chance, and Probability
Gambling involves uncertain outcomes and gambling was a
primary motivation for early studies of probability. Games of chance are
easily analyzed using classical probability methods. Casino gambling and
online gambling are both growing industries, despite the fact that the games
they offer are not fair bets. (The expected value of the bet is negative;
if you play long enough you will lose all of your money.)
This edge to the house makes possible the gambling palaces of
A number of websites offer basic analysis of casino games but they are so gimmicked with pop-up windows and promotions that I'm reluctant to include them here. Try Yahoo's gambling section for a selection. Wizards of Odds is interesting.
Life expectancy is an another interesting example of expected value. Since expected values are based on probabilities, we can improve these calculations with more information. In other words, we can use conditional probabilities to more accurately estimate lifespans. Northwestern Mutual Insurance has a fun website: try their Longevity Game .
Financial markets also display large amounts of uncertainty. The theory of efficient markets concludes that changes in stock prices should be random and unpredictable. This means returns from a portfolio will be more uncertain than a salesman at a brokerage would like you to believe.
IV. Analyzing data
Numbers by themselves are boring. They only have interest in the context of a research question. Hypothesis testing is a statistical way to answer questions like, "does Energizer last longer? " or "do tax cuts increase consumer spending?" For some questions we can compare populations. For other questions we want to relate variables using correlation or regression . Sometimes we will look for trends and cycles using time series analysis .
V. What else can we do?
Regressions are frequently used for forecasting. Many economic variables are interconnected, so forecasters build systems of equations to make forecasts. Fairmodel is a large macromodel (US or international) available for free, online.
Tests and projects
We will have two midterms and a final-- each with a variety
of types of questions. The material on each exam will be discussed in
Exam I Wednesday, January 30 7:00 pm (4th week)
Exam II Monday, February 25 7:00 pm (8th week)
Exam III Tuesday, March 19 1:30 pm (Final exam week)
Class Blog page: http://www.kalamazoostatistics.blogspot.com/
We'll also have assignments, quizzes, and problem sets throughout the term.
Throughout the quarter we work on original research projects . I'm including links to previous class projects below. (please note: these are web summaries of the project-- the online version may be missing elements included in the original paper.) These classes had different assignments, as well. Studies Winter 2002 , Stats Research Spring 2002 , Stats Projects Fall 2002 , Statistical Projects Spring 2003 , Research Projects Winter 2004, Research Projects Spring 2004, Research Projects Winter 2005, Research Projects Spring 2006
A textbook website:
The Practice of Business Statistics by David Moore, George McCabe, William Duckworth, Stanley Sclove; W.H. Freeman and Company, 2003. The website has an unusual amount of useful material including statistical animations .
a few statistical sources:
The Gallup Poll
Federal Statistics (from 70 agencies)
Microeconomic datasets from
EconDash discusses economic measurement and data
A website to accompany Statistics: Concepts and Controversies has some fun java applets illustrating various statistical concepts.
John Allen Paulos (
The Data and Story Library
Data for Problem Set #1 Fall 2002 (Excel file)
Data for Problem Set #2 Fall 2002 (Excel file)
Questions, problems, or comments?