Course: B01.1305.61 - Statistics and Data Analysis
Semester: Summer 2002
Class Hours: H 6:00 to 9:30 PM
Class Room: KMC 3-70

Instructor: Professor Aaron Tenenbein
Office: KMC 8-58 Tel: (212) 998-0474
Email: atenenbe@stern.nyu.edu

A. COURSE DESCRIPTION

The purpose of this course is to provide a survey of probability and statistics which areapplicable to decision making in a business environment. The course stresses applications; the technical aspectsunderlying the applied methods used will be presented intuitively.

The first topic is a review of Data Collection and Analysis. This topic discusses the methodologyinvolved with extracting information for data which are collected and using these data to aid in the decision makingprocess.

The second topic involves a discussion of probability and probability distributions. Asmany business decisions have to be made in the face of uncertainty, it is very important to understand the appliedconcepts of probability in order to aid the decision making process.

The next topic is Sampling and Statistical Inference. In most cases business decisions willhave to be made by using information from sample surveys. The key question is how to determine the reliabilityof the sample information. The concepts of probability are used to answer these questions so that the informationcontained in the sample can be used to infer the information required.

The next topic is regression analysis and forecasting. This topic is probably one of themost important and widely used statistical techniques. It has a wide variety of applications to business problemsin accounting, economics, finance, management, marketing, and operations. Generally regression analysis is involvedwith the prediction or forecasting of a given variable (called the dependent variable) given knowledge of the valuesof other variables (known as the independent variables). In marketing, a media buyer would like to measure theimpact of advertising and other variables on sales. A financial analyst may want to predict the return on a stockfrom the return on an index. A production engineer may want to predict the time it takes to complete a given taskfor given characteristics of that task.

Closely associated with regression analysis is correlation analysis which is concerned withthe measurement of the relationship between different variables. This can be used to study such things as the correlationbetween advertising and sales of a product and between the rate of return of a stock fund and the rate of returnof a bond fund. Obviously correlation and regression analysis are closely related.

The computer will be used extensively as an aid for performing analyses on cases which areprovided. No computer programming background is necessary and instructions for the use of the computer packageMINITAB on the IBM PC will be provided.

The course will be taught in a lecture and discussion mode. Student participation is stronglyurged.

1. H: Hildebrand, David K., and Ott, R. Lyman (1996), Basic Statistical Ideas for Managers, New York: Duxbury Press.
2. C: Course Supplement.

NOTE: Reading 1 should be purchased from the Book Store.

C. PROBLEM ASSIGNMENTS AND TESTS

Problem assignments will be given weekly. Many of these problems assignments involve theuse of the computer. Two examinations will be scheduled. The basis for the grade is as follows:

 Category Percentage Assignments and Group Participation 15% Midterm Examination 35% Final Examination 50%

D. COURSE TOPICS AND READING ASSIGNMENTS

 TOPICS READING ASSIGNMENTS 1. Data Collection and Analysis H: Chapters 1-2  H: Chapter 11: Sections: 1,2,5 2. Probability and Probability Distributions  (Including the Binomial and Normal Distribution) H: Chapter 3: Sections: 1,2  H: Chapter 4: Sections: 1,2,3  H: Chapter 5: Sections: 1,2,4 3. Sampling and Statistical Inference H: Chapter 6: Sections: 1,2,3  H: Chapter 7: Sections: ALL  H: Chapter 8: Sections: 1,3,4,5 4. Correlation Analysis, the Simple Regression Model and Multiple Linear Regression Models H: Chapters 11-13

Page Design and Maintenance by pcariaso@stern.nyu.edu