Honors | Statistical Analysis of Business & Economics - Honors
S370 | 1657-1658 | M. Kaganovich

9:30-10:45am  MW  WY 115
9:30-10:45am  MW  WY 125
11:15-12:30pm MW  WY 115
11:15-12:30pm MW  WY 125

Required Computer Program:  Microsoft Excel
This program is available through the Spreadsheets submenu in all the
IUTS clusters.  Statistical applications of this computer package will
be emphasized in this class. Most of assignments and exams will be
computer-based, and the knowledge of  EXCEL=s  statistical
applications will be required.  Familiarity with the most basic
spreadsheet commands in EXCEL is assumed.

Prerequisites:  M118 (Finite Mathematics) or equivalent completed
prior to this class is an absolute requirement.  At least concurrent
enrollment in a calculus class (the M119 level or above) is also

Course Objectives
This class builds on your overall quantitative concepts and skills, as
well as on the knowledge of basic probability and statistics you
obtained in your Finite Math class.  This class should substantially
enhance this very important component of your college education.  It
will provide - the understanding of key statistical concepts used in
economics and business;
- the knowledge of basic statistical methods of data analysis which
are rigorously founded in the theory    of probability, and the
ability to apply these methods with the help of statistical tools
available on computer;
- the ability to draw statistical inferences, i.e., to interpret the
results obtained from the application of statistical methods.

The course will cover the following topics:
Descriptive Statistics.
Basic Rules of Probability: a brief review, knowledge presumed within
the scope of M118. Random Variables, Expected Values (knowledge of the
basics within the scope of M118 is presumed).

Finance applications are emphasized. Advanced topic: Expected Utility
and decisions under uncertainty Probability Distributions (the most
essential are:
Binomial and Normal distributions) Sampling Distribution of sample
means and proportions Point and Interval Estimation Hypothesis Testing
Simple Linear  Regression and Correlation
Multiple Linear Regression