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Canyon College

COURSE SYLLABUS: BU580 - Quantitative Methods

Course Title:	BU580 - Quantitative Methods
Department:	Education
Instructor:	Sol Drescher, Ph.D., B.B.A., E-Mail -- Vita

Required Texts  Online Bookstore

Douglas A. Lind, William G. Marchal, Samuel A. Wathen, Statistical Techniques in Business and Economics, 12th edition. McGraw Hill Publisher
ISBN: 0072868244

There are student workbooks that accompany the text that will assist students with exercises.

This text comes with statistical software called Megastat. It is a software program that is an add-in to Excel that will perform statistical functions for you very rapidly. It is highly recommended that students take advantage of the productivity that this software offers.

For those that have Excel expertise, Excel has many statistical functions on its own but Megastat makes them much easier to use. Students without any familiarity with Excel might consider the following text as well to assist them

ISBN: 0072868287: Douglas A. Lind, William G. Marchal, Samuel A. Wathen, Basic Statistics Using Excel for Office XP McGraw Hill Publisher

Catalog Course Objective

This course is for students who are only interested in learning the basic principles of quantitative methods for applying in business operations. The emphasis is gaining knowledge and understanding of the principles of statistics.

Course Objectives

At the end of this course, you should be able to demonstrate knowledge and understanding of the topics covered.

Topics to be covered:

Probability and Probability Distributions

• Identify basic probability terminology and concepts.
• Examine the rules of probability covering addition and multiplication (general and special rules).
• Distinguish between a discrete probability distribution and a continuous probability distribution.
• Demonstrate an understanding of the expected value and standard deviation for a discrete probability distribution.
• Demonstrate an understanding of the basic characteristics of the binomial probability distribution, and cite examples illustrating its importance in decision making.
• Examine the basic characteristics of the Poisson probability distribution, and cite examples illustrating its importance in decision making.

Normal Distribution

• Distinguish between a discrete probability distribution and a continuous probability distribution.
• Define the basic characteristics of the normal probability distribution, including the Z statistic and the standard normal distribution, and cite examples illustrating their importance in decision making.
• Compare and contrast different business situations requiring probability distributions, and identify the type of probability distribution that would be used in decision making.

Confidence Intervals

• Demonstrate an understanding in constructing confidence interval estimates for means and proportions.
• Describe the minimum required sample size for both means and proportions based on allowable error, degree of confidence, and assumed variance.

Hypothesis Testing

• Examine the concept of hypothesis testing.
• Demonstrate an understanding of the hypothesis-testing procedure used for research problems.
• Distinguish between a one- and a two-tailed test.
• Demonstrate an understanding for hypothesis tests for a population mean and for a population proportion.
• Discuss the p value approach to hypothesis testing.
• Distinguish among Type I error, Type II error, and a good decision.

ANOVA

• Demonstrate the F Test for differences of two population variances.
• Explain the difference between one and two factor ANOVA and determine which is the most appropriate test for the business research application.
• Demonstrate an understanding of testing three or more group means at one time; evaluate the output of the statistical tests; and determine if additional analysis is warranted.

Linear Regression and Correlation

• Demonstrate an understanding of simple regression model and its use in prediction.
• Explain correlation and test the significance of that relationship; interpret the results from both manual calculations and computer output. Determine if a relationship exists between the two variables, and the direction of that relationship.
• Explain the multiple regression model and its use in predicting events.
• Explain the use of dummy variables in a regression analysis and their interrelationship with other quantitative variables, and interpret their impact on the model.
• Explain the importance of multicollinearity and autocorrelation in a multiple regression analysis, and the various methods for controlling them.

Multiple Regression Analysis

• Explain the multiple regression model and its use in predicting events.
• Explain the use of dummy variables in a regression analysis and their interrelationship with other quantitative variables, and interpret their impact on the model.
• Explain the importance of multicollinearity and autocorrelation in a multiple regression analysis, and the various methods for controlling them.

Analysis of Categorical Data

• Explain the use of the chi-square goodness-of-fit test and interpret the output.
• Demonstrate an understanding of the chi-square test of independence.

Expectations

As an on-line course you are expected to study the topic, work on problems from the text. The text contains the answers to the odd numbered problems as an appendix. Further problems are available in a student workbook that can be acquired to accompany the text.

Students will take a Mid-term and Final Exam which will demonstrate their knowledge of the material.

Operating Directions

• This is a self-paced course guided by the instructor. Plan to complete all work 8 weeks.
• You may use other statistics texts in addition to readings the textbook.
• Submit all exercises as MS Word or Excel as email attachments.
• You are required to be ethical as required by educational institutions.

Contact

Main Email: drsol@canyoncollege.edu

Letter Grade Determination

A 89 - 100
B 79 - 88
C 69 - 78
D 60 - 68
F 0 - 59