DOMINICAN UNIVERSITY

SCHOOL OF BUSINESS

Fall 2003          BAD260-03              INTRO TO STATISTICAL METHODS                                    Syllabus

INSTRUCTOR: Robert Irons                                                           OFFICE HOURS: 12:00 – 1:00 PM S  

PHONE: Work (847) 888-6544                                                                FAX: (847) 888-5410        

EMAIL: rirons25@hotmail.com

 

 

PLEASE SHUT OFF ALL CELL PHONES AND PAGERS PRIOR TO THE BEGINNING OF EACH CLASS PERIOD.

                

 

CLASS MEETS:             Class will meet from 9:00 AM to 12:00 PM each Saturday.

 

PREREQUISITES:             None

 

TEXTBOOK:             Practical Business Statistics, Fifth Edition, Andrew F. Siegel,

                                    McGraw-Hill Irwin, 2003, with CD-ROM

 

OTHER MATERIALS: Students must bring a hand-held calculator to every class. Students must have access to a computer loaded with Microsoft Excel. Students must be proficient in the use of their own calculator and a PC. Experience with MS Excel is desirable but not necessary. Students must also have access to email and the internet.

 

COURSE OVERVIEW: This course is designed to provide an overview of the basic concepts and principles of descriptive and inferential statistics with an emphasis on their application in the practice of business. The material is structured to teach students to think analytically and critically about business problems that lend themselves to quantitative analysis. Theoretical material will be supplemented with problems solved using Microsoft Excel and with business cases, all of which will help students develop essential problem-solving skills necessary to deal with ambiguity in the real business world.

 

LEARNING OBJECTIVES:

1.      Appreciate the ethical issues associated with data analysis and its use in managerial decision-making.

2.      Develop graphical and numerical depictions of datasets (charts, histograms, scatter diagrams, etc.).

3.      Calculate and interpret descriptive and inferential statistics.

4.      Develop and analyze probability distributions using real-world data.

5.      Understand the issues involved in drawing samples to represent a population.

6.      Apply confidence intervals and hypothesis tests to make decisions about population characteristics based upon samples.

7.      Communicate statistical analysis effectively to others in written and verbal formats.

8.      Conduct and analyze regression models and other types of forecasting models (moving average, exponential smoothing, time series, etc.).

9.      Develop data analysis skills using Microsoft Excel.

 

GRADING POLICY:

There will be three exams, in-class using a calculator. There will be homework assigned for each chapter, some requiring hand calculation and some requiring Excel, which will be due the class period following the lecture. There will be three cases assigned that will require you to analyze data and write reports on your findings. Points for assignments will be given as follows: 

 

                       

Homework (total)

150 points

Cases (50 pts. each)

150 points

Exam I

100 points

Exam II

100 points

Exam III

100 points

Total

600 points

 

           

A

> 558 points

A-

540 - 558

B+

522 - 539

B

498 - 521

B-

480 - 497

C+

462 - 479

C

438 - 461

C-

420 - 437

D+

402 - 419

D

378 - 401

F

< 378 points

 

 

CASE ANALYSIS

The following steps should be used as a guide whenever analyzing a case (simpler cases will not require all of these steps):

 

1.      Graph what you can in Excel (bar charts, pivot tables, etc.) in order to visually assess the data.

2.      Run descriptive statistics (Tool – Data Analysis – Descriptive Statistics). Be sure that the data “count” includes all of your data (unless outliers are identified and intentionally removed).

3.      Interpret the following:

a.      Is the mean valid? (skewness, kurtosis)

b.      Z score (measure the outliers)

c.      Standard deviation

d.      Range

e.      Chebyshev’s Empirical Rule

f.        Quartiles

g.      Correlation coefficient (covariance and coefficient of variation if needed)

4.      Scatter diagrams

a.      Add trend line

b.      Interpret R2, slope and intercept

5.      What additional data is needed in order to evaluate the problem more effectively? How is the managerial function helped or enhanced by this study?

 

Write-ups for the cases should be professional (spelling, grammar and sentence construction count!), coherent and concise. Address the memo to a specific person or group, including title (make one up if necessary), and design the paper to that individual (or group). Include all tables, graphs and calculations in your paper (embed tables and graphs from Excel in the Word document if possible). Include an executive summary at the beginning of the document and a summary at the end. Write the memo using the following (simplified) format:

 

A.     Tell them what you are going to tell them;

B.     Tell them;

C.     Tell them what you told them.

 

NOTE: Cases presented must be entirely original material (any references to previously published material must be fully credited). Plagiarism is a serious infraction, and will not be tolerated. Students determined to have plagiarized any portion of their work will receive a failing grade for the class, and the incident will be reported to the administration to become part of their permanent record. Work determined to have been copied from another student will be treated in the same way.

 

 

OPERATING POLICIES:

 

1.      The nature of this course makes your individual effort and preparation outside class very important. Reading the chapter before the lecture will help in understanding the lecture better. Except for the first class, LECTURES WILL BE GIVEN WITH THE ASSUMPTION THAT THE TEXT MATERIAL HAS ALREADY BEEN READ.

2.      The grade of Incomplete (I) will be awarded only in documented cases of medical incapacitation or other extraordinary conditions at the time of the final class date, provided such documentation is provided prior to the final class date, and only to a student with satisfactory performance at the time the Incomplete grade is requested.

3.      Make-up exams will be given only under the most serious circumstances, and then only if given prior notification. Absence from an exam without prior notification of the instructor will result in an automatic F for that exam.  Students caught cheating on an exam will receive an automatic F for that exam.

4.      Attendance is not mandatory, but will be taken into consideration when arguing for points or when a grade is “on the bubble.” Homework is due the week following the lecture, and must be handed in on time – no late homework or cases will be accepted. In the case of absence, work can be turned in by a fellow student or via email, but must be on time.

5.      Students are expected to take notes in class as well as to read the assigned material. Exam questions may come from the lecture material as well as from the text.

6.      Students must bring their own calculators to class. Sharing of calculators during exams will not be permitted.

7.      The instructor reserves the right to modify this syllabus if necessary.

COURSE OUTLINE:

                                                           

Chapter

Topic

Homework

1

Introduction: Defining the Role of Statistics

None

2

Data Structures

Problems 7 and 8, Page 48.

Database Exercises 1 and 2, Page 53.

3

Histograms

Problems 1 through 5, pages 85-86.

Excel: Problems 6 and 9, pages 86-88.

4

Landmark Summaries: Interpreting Typical Values and Percentiles

Problems 5, 6, 7, 21 and 22, pages 131-136.

Excel: Database Exercises 1, 2 and 3, page 140.

CASE 1: Managerial Projections for Production and Marketing, pages 141-143

5

Variability

Problems 9, 12 and 13, pages 175-176.

Excel: Database Exercises 1 and 2, page 183.

 

Exam I: Chapters 1 - 5

 

6

Probability: Understanding Random Situations

Problems 10, 11, 12, 17and 22, pages 227-229.

Excel: Database Exercise 1, page 233.

Case 1 is due

7

Random Variables: Working with Uncertain Numbers

Problems 2, 4, 10 11 and 22, pages 275-279.

Excel: Database Exercises 1 and 2, page 282.

CASE 2: The Option Value of an Oil Lease, pages 283-284.

8

Random Sampling

Problems 18, 19, 20 and 44, pages 321-327.

Excel: Database Exercises 2 and 3, Pages 327-328.

9

Confidence Intervals

Problems 2, 3, 11 and 26, pages 363-366.

Excel: Database Exercises 1 and 2, page 371

10

Hypothesis Testing

Problems 3, 8, 46 and 48, pages 418-429.

Excel: Database Exercises 2 and 4, page 430.

 

Exam II: Chapters 6 – 10

 

11

Correlation and Regression

Problems 2 and 9, pages 494-498.

Excel: Problems 34 and 38, pages 506-509; Database Exercises 1 and 2, page 510.

Case 2 is due

12

Multiple Regression

Excel: Problems 12 and 28, pages 584-593; Database Exercises 1 and 2, page 593.

CASE 3: Controlling Quality of Production, pages 595-597.

16

Nonparametrics

Problems 3, 5, 6, and 8, pages 721-723.

Excel: Database Exercises 2 and 3, page 725.

 

Exam III: Chapters 11, 12 and 16

Case 3 is due

                      

Homework will be due the class period following the lecture covering the material in question. Excel work must be turned in on a diskette for via email. All files and diskettes must be scanned for viruses prior to turning them in – failure to do so will result in an F for the assignment. Cases are due as posted on the above schedule.