NYU Stern School of Business

Undergraduate College

STAT-UB.0003.005 (C22.0003): REGRESS/FORCASTING MODEL

Spring 2013

Instructor Details

Shahmaei, Ardeshir

ashahmae@stern.nyu.edu

212 998 0828

T,R 10:00 – 11:00 Am, and by appointment

KMC -171B

 

Course Meetings

TR, 11:00am to 12:15pm

Tisch T-UC15


Final Exam:

Schedule exceptions
    Class will not meet on:
    Class will meet on:

 

Course Description and Learning Goals

The objective of this course is to introduce students to the basic statistical techniques which are widely used in business and other fields. In particular considerable attention will be devoted to the technique of regression analysis, which is a useful and powerful technique for modeling the relationships between variables of interest.

 

Course Pre-Requisites

V63.0121 - Calculus 1, 4 credits

 

 

 

 

 

 

 

 

 

 

Course Outline

 

Topical Outline:

The abbreviation MBS below refers to McClave, Benson, and Sincich, the course textbook.

Topical Heading / Date

Specific Topics

Readingsand Homework

Assignment due

Simple linear regression  Date: T 3/26/13

Introduction,  Hypothesis testing review                                  10.1, 10.2  Probabilistic Models                              Fitting the Model

 MBS, Chapter 10                                                                        Exercises: 10.18, 10.20                                                 

 

Simple linear regression  Date: R 3/28/13

10.3 -10.4 Model assumptions, Inferences about.

MBS, Chapter 10                                                                      Exercises:10.33, 10.40, 10.44                                                   

                                                                

Simple linear regression  Date: T 4/2/13

10.5  The Coefficient of Correlation   and Determination                      

 MBS, Chapter 10                                                                        Exercises:    10.64                                                   

Handout assignment I

Simple linear regression  Date: R 4/4/13

10.6, 10.7 Using the Model for Estimation and Prediction

MBS, Chapter 10                                                                        Exercises:  10.70, 10.98                                                    

 

Simple linear regression  Date: T 4/9/13

Beta Coefficient, and Residual Analysis

         

 

Simple linear regression  Date: R 4/11/13

Review

 

Handout assignment II

Mid-term Exam       Date: T 4/16/13

Material covered in classes 1-6

 

 

Multiple regression        Date: R 4/18/13

 Multiple Regression Model   Interpretations of coefficients 

MBS, Chapter 11                                                         

 

Multiple regression        Date: T 4/23/13

11.2, 11.3 Inferences about Parameters, Overall Model Utility.

MBS, Chapter 11                                 Exercises: 11.7, 1120

 

Date: R 4/25/13

11.4, 11.12 Using the Model for Estimation and Prediction, Multicollinearity.   

MBS, Chapter 11                                 Exercises: 11.27, 11.117

Handout assignment III

Multiple regression        Date: T 4/30/13

11.5, 11.7, 11.8 Quadratic Models,

MBS, Chapter 11                                 Exercises: 11.62, 11.116

 

Multiple regression        Date: R 5/2/13

11.8 Qualitative (Dummy) Variables Models.   

MBS, Chapter 11                                 Exercises: 11.103

Handout assignment IV

Multiple regression        Date: T 5/7/13

11.9 Comparing Nested Models model.    Review

 

 

Final Exam              Date: R 5/9/13

                                                                   

 

 

 

Required Course Materials

Text:

1. Statistics for Business and Economics, 11th edition, by McClave, Benson, and Sincich (MBS), Prentice Hall. Chapter 10 and 11 in the MBS custom version will be covered. 
The text (MBS), and Student's Solutions Manual are sold as one package at the NYU Main Bookstore on 18 Washington Place, though you may choose to use copies of relevant materials from previous classes.

2. Lecture Notes/slides and Handouts (will be posted on Blackboard).

 

Computer Software and Data Sets:

Statistical computing will be done with the program Minitab 16 for Windows.  This program runs on the Stern network; individual copies can be purchased from the Professional Bookstore. The latest release number of Minitab for Windows is 16.  Data files required for the assignments will be available from http://www.stern.nyu.edu/~gsimon/statdata. Many of the data files are from the disk that accompanies the textbook

 

Assessment Components

Grading Information:

                                                                                                                                             

Exams will be given in class and are not comprehensive in that they only cover material developed since the preceding exam. 

 

Mid-term Exam

40%

Final Exam

40%

Homework & Attendance

20%

 

 

Assignments:

Homework will be drawn from exercises from the textbook. These exercises are listed in the third column on the next page. Data files required for the exercises are found on the disk that accompanies the textbook Blackboard and will be posted on. The exercises will be reviewed during the following class. Additional homework may be assigned. Handout assignments will be posted on Blackboard. Your solutions for the handout assignments will be collected at beginning of the class on the due dates. The due dates are listed in the fourth column on the next page. It is essential that each student understands and solves the assigned problems.              Late assignments will not be accepted.

 

Grading

The grades for this course follow the Stern Grading Guidelines for Core Courses at the Undergraduate College.

 

Professional Responsibilities For This Course

CLASSROOM POLICIES:

Please arrive promptly for the start of class.  Late entrances are disruptive to the discussion.   Also, pleaseremember to turn off cell phones. 

 Entering (leaving) the classroom late (early) may be very disturbing for your fellow students.  If you do have to come late or leave early,   please do so as unobtrusively as possible (if there is a backdoor, you use the backdoor; avoid the middle aisle, etc.). 

Please do not use laptop computers in class.  If you have a special need for a laptop, please consult Professor Shahmaei.

 

Stern Policies

General Behavior
The School expects that students will conduct themselves with respect and professionalism toward faculty, students, and others present in class and will follow the rules laid down by the instructor for classroom behavior.  Students who fail to do so may be asked to leave the classroom. 

 

Collaboration on Graded Assignments
Students may not work together on graded assignment unless the instructor gives express permission. 

 

Course Evaluations
Course evaluations are important to us and to students who come after you.  Please complete them thoughtfully.

 

Academic Integrity

Integrity is critical to the learning process and to all that we do here at NYU Stern. As members of our community, all students agree to abide by the NYU Stern Student Code of Conduct, which includes a commitment to:

The entire Stern Student Code of Conduct applies to all students enrolled in Stern courses and can be found here:

Undergraduate College: http://www.stern.nyu.edu/uc/codeofconduct
Graduate Programs: http://w4.stern.nyu.edu/studentactivities/involved.cfm?doc_id=102505

To help ensure the integrity of our learning community, prose assignments you submit to Blackboard will be submitted to Turnitin.  Turnitin will compare your submission to a database of prior submissions to Turnitin, current and archived Web pages, periodicals, journals, and publications.  Additionally, your document will become part of the Turnitin database.

 

Recording of Classes

Your class may be recorded for educational purposes

 

Students with Disabilities

If you have a qualified disability and will require academic accommodation of any kind during this course, you must notify me at the beginning of the course and provide a letter from the Moses Center for Students with Disabilities (CSD, 998-4980, www.nyu.edu/csd) verifying your registration and outlining the accommodations they recommend.  If you will need to take an exam at the CSD, you must submit a completed Exam Accommodations Form to them at least one week prior to the scheduled exam time to be guaranteed accommodation.

 

Group Projects

Guidelines for Group Projects

Business activities involve group effort. Consequently, learning how to work effectively in a group is a critical part of your business education.

Every member is expected to carry an equal share of the group’s workload. As such, it is in your interest to be involved in all aspects of the project. Even if you divide the work rather than work on each piece together, you are still responsible for each part. The group project will be graded as a whole:   its different components will not be graded separately. Your exams may contain questions that are based on aspects of your group projects.

It is recommended that each group establish ground rules early in the process to facilitate your joint work including a problem-solving process for handling conflicts. In the infrequent case where you believe that a group member is not carrying out his or her fair share of work, you are urged not to permit problems to develop to a point where they become serious. If you cannot resolve conflicts internally after your best efforts, they should be brought to my attention and I will work with you to find a resolution.

You will be asked to complete a peer evaluation form to evaluate the contribution of each of your group members (including your own contribution) at the conclusion of each project. If there is consensus that a group member did not contribute a fair share of work to the project, I will consider this feedback during grading.

 

Re-Grading

The process of assigning grades is intended to be one of unbiased evaluation. Students are encouraged to respect the integrity and authority of the professor’s grading system and are discouraged from pursuing arbitrary challenges to it.

If you believe an inadvertent error has been made in the grading of an individual assignment or in assessing an overall course grade, a request to have the grade re-evaluated may be submitted. You must submit such requests in writing to me within 7 days of receiving the grade, including a brief written statement of why you believe that an error in grading has been made.

 

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