Hofstra University

Frank G. Zarb School of Business

 

“to provide students with a perspective on the integration of the functional areas of business, while

maximizing the use of analytical skills and knowledge for decision making in a

contemporary global business environment”

 

Department of BCIS/QM

Quantitative Methods 122 – Intermediate Business Statistics

Undergraduate Course

 

 

Instructor’s Name:                               Lonnie K. Stevans

Office Hours:                                       11:15 A.M. – 12:15 P.M., M-W-F

Location of Office:                               111 Weller Hall

Extension:                                            35375

Home Number:                                    631-598-8518

Fax:                                                      631-264-0730

E-Mail Address:                                   acslks@hofstra.edu

Web Page:                                            http://www.i2.i-2000.com/~acslks/lks.html

 

General Information:

 

Location of Department Office:           211 Weller Hall

Extension:                                            35716

Department Chairperson:                     Dr. John Affisco

 

Description of Course:

 

Builds upon and continues the work introduced in QM 001.  Topics include statistical quality

control, chi-squared tests and the analysis of contingency tables, simple and multiple regression,

correlation, and time series models with applications to business forecasting.

 

Prerequisites:

 

QM 001, BCIS 010 or 014

 

Required Text:

 

Statistics for Business and Economics, 9th Edition, by Anderson, Sweeney, and Williams.

 

Computer Proficiency Required:

 

It is expected that the student will have an elementary knowledge of Blackboard and the Windows

Operating System.

 

Outcome Objectives and Methods of Achieving the Objectives:

 

To acquaint the student with the use of Minitab in analyzing business and economic problems. 

Upon completion of this course, a student should be able to perform intermediate statistical

analyses using Minitab.  The instructor will lecture on individual chapters and assign homeworks

that will be done on Blackboard.

 

Attendance Policy:

 

Attendance is required for satisfactory completion of the course.

 

Method of Evaluation:

 

Students are required to read all assigned chapters and do all assigned homeworks.  Late assignments

will not be accepted beyond the date that they are due.  Homeworks on Blackboard will be made

available until 8:00 A.M. the day that they are due.  A midterm and a final exam will be given:

 

                        Computer Assignments:              15 %

                        Midterm Exam:                          40 %

                        Final Exam:                               45 %

 

School of Business Policy on Makeup Examinations:

 

To be eligible for a makeup examination, a student must submit to the instructor written documentation

of the reason for missing a scheduled examination due to medical problems or death of an immediate

family member.  The instructor (not the student) determines whether and when a makeup is to be

given.  If a makeup examination is to be given, the instructor will determine the type of makeup

examination.  If the student misses (for any reason) the scheduled makeup examination, additional

makeups are not permissible.

 

University Policy on Incomplete Grades:

 

A student unable to complete a course may, with the permission of the instructor, receive a grade

of incomplete (INC).  The instructor will permit the student to compete and submit the missing work

no later than the third week of the following semester.  All undergraduate students may accumulate

up to nine credits of INC grades without penalty.  Past this nine-credit limit, all subsequent INC

grades not made up will convert to Fs at the end of the semester following the one in which they

were assigned.

 

Course Outline:

 

                                                                                                            Chapters

 

            I.          Review                                                                         6, 7, 8, 9

 

            II.         Tests of Goodness of Fit and Independence                     12

 

III.       Simple Linear Regression                                               14

 

IV.             Midterm Exam

 

             V.        Multiple Regression                                                        15

 

VI.       Model Building                                                              16

 

VII.      Statistical Methods for Quality Control                            20

 

            VIII.     Forecasting                                                                    18

 

            IX.       Final