MASTER COURSE SYLLABUS
Date: August 2002
Course Number: MSC 287
Course Title: Business Statistics I
Instructor(s): Stafford, Tseng
Typical Textbook: Anderson, D.R., Sweeney, D.J., and Williams, T.A., Modern Business Statistics with Microsoft Excel , 1st ed., 2003, South-Western.
Catalog Description: Introduction to the concepts of probability and business statistics. Topics include: tabular, graphical, and numerical methods for descriptive statistics; measures of central tendency, dispersion, and association for sets of data; probability; discrete and continuous probability distributions; the use of calculus in statistics; sampling and sampling distributions; an introduction to confidence intervals. The solution of problems using spreadsheets is integral and mandatory for this course. This course is a prerequisite for MSC 288. Lab Fee: Level 2.
Prerequisites: MIS 146, MA 145, or equivalents.
Course Objectives: To provide an understanding and a working knowledge of: (1) the tools of descriptive statistics; (2) the basics of probability theory; (3) the theory and application of probability distributions used in business problem solving; (4) the normal distribution; and (5) sampling distributions and their relationship to statistical inference; and (6) to develop proficiency in solving basic statistical problems using computer spreadsheets.
Computer Usage: Excel or other spreadsheet software will be used to compute various graphical and descriptive statistics for qualitative and quantitative data sets. Solution of problems by writing the functions in Excel enhances the students’ learning of these topics. The computer is used in this course to collect, edit, summarize, and analyze statistical data. This computer usage prepares the student for follow-on computer analyses in MSC 288, MSC 385, and other advanced courses.
Global Issues: Limited to examples from the international business world.
Business Ethics: Discussions of the ethical and unethical uses of various statistical tools are woven into the course lectures. Real-world examples of misuse of statistics are presented.
Demographic Diversity: Not an appropriate topic for this basic course.
Technology: This course utilizes the latest student-friendly technology to support learning. Managing technology is not an appropriate topic for this basic course.
MASTER COURSE SYLLABUS MSC 287 August 2002
Environmental Issues: Not an appropriate topic for this basic course.
Research Paper: Not applicable.
Subject Matter: (based on 28 80-minute sessions)
Item Sessions
1. Introduction to Statistics 2.0
Business Applications; Vocabulary; Data Sources; Scales of Measurement
2. Graphical Methods for Describing Data 2.0
Summarizing Qualitative and Quantitative Data: Frequency Distributions, Histograms, Bar Graphs, Stem-and-Leaf Displays, Cross tabulations
3. Numerical Methods for Describing Data 3.0
Measures of Location: Mean, Median, Mode, Percentiles; Measures of Dispersion: Range, Variance, Standard Deviation; Uses of the Mean and Standard Deviation: Z-scores, Chebyshev's Theorem, Empirical Rule; Measures of Association between Two Variables: Covariance and Correlation
4. Introduction to Probability 5.0
Vocabulary and the Sample Space; Methods of Assigning Probabilities; Events and Their Probabilities; Basic Probability Relationships; Conditional Probability; Bayes' Theorem
5. Discrete Probability Distributions 4.0
Random Variables: Discrete and Continuous; Expected Value and Variance; Discrete Probability Distributions: Binomial, Poisson, and Hyper geometric
6. Continuous Probability Distributions 4.0
Expected Value and Variance: Calculus in Statistics; Uniform and Exponential Probability Distributions; The Normal Probability Distribution; Normal Approximation of Binomial Probabilities
7. Sampling Distributions 2.0
Simple Random Sampling; Introduction to Sampling Distributions; Sampling Distribution
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of X; Central Limit Theorem; Sampling Distribution of p ; Other Sampling Methods.
8. Introduction to Interval Estimation and Hypothesis Testing 2.0
Interval Estimation of a Population Mean: Large- and Small-Sample Cases; Interval Estimation of a Population Proportion; Determining Sample Sizes; Null and Alternative Hypotheses; Type I and Type II Errors; Large-Sample Tests about a Population Mean: One- and Two-Tail Tests
9. Examinations, Computer Instruction and Review 4.0