NYU Stern School of Business

Undergraduate College

STAT-UB.0003.001 (C22.0003): REGRESS/FORCASTING MODEL

Fall 2011

Instructor Details

Shahmaei, Ardeshir

ashahmae@stern.nyu.edu

212 998 0828

Tuesday Thursday 2 - 3 pm

KMC 8-171B

 

Ki Young Kim

kyk229@stern.nyu.edu

1 831 236 7922

TBA

The Ernst and Young Learning Center

 

Course Meetings

TR, 3:30pm to 4:45pm

KMC 4-120



 

Course Description and Learning Goals

Objective: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 a 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

Students taking C22.0003 will be required to have mastered the material in C22.0001.

 

Course Outline

Course Outline

Topical Heading / Date

Specific Topics

Readingsand Homework

Assignment due

Simple linear  regression 
Date: Tu 9/6/11

Introduction,                                   
10.1, 10.2  Probabilistic Models
Fitting the Model

MBS, Chapter 10
Exercises:   10.18, 10.20                                                  

 

Simple linear regression 
Date: Th 9/8/11

10.3 -10.4 Model assumptions, Inferences  about Coefficient.

MBS, Chapter 10                                                                        Exercises:   10.33, 10.40, 10.44                                                   

                                                               

Simple linear regression 
Date: Tu 9/13/11

10.5  The Coefficient of Correlation and Determination                      

 MBS, Chapter 10                                                                        Exercises:    10.64                                                  

 

Simple linear regression 
Date: Th 9/15/11

10.6, 10.7 Using the Model for
 Estimation and Prediction

MBS, Chapter 10                                                                        Exercises:  10.70, 10.98                                                    

 

Simple linear regression 
Date: Tu 9/20/11

Elasticity, Beta Coefficient, and Residual  Analysis,

Handout               

 

Simple linear regression 
Date: Th 9/22/11

Review:

 

Handout assignment I

Mid-term Exam      
Date: Tu 9/27/11

Material covered in classes 1-6

 

 

Multiple regression      
Date: Th 9/29/11

11.1 Multiple Regression Model
   Interpretations of coefficients                            

MBS, Chapter 11                                    Exercises:                      

 

Multiple regression        
Date: Tu 10/4/11

11.2, 11.3 Inferences about Coefficient Parameters, Overall Model Utility.

MBS, Chapter 11                                 Exercises: 11.7, 1120

 

Multiple regression       
Date: Th 10/6/11

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

MBS, Chapter 11                                 Exercises: 11.27, 11.117

 

Date: Tu 10/11/11

No Class

 

 

Multiple regression       
Date: Th 10/13/11

11.5, 11.7, 11.8 Quadratic Models, Qualitative (Dummy) Variables Models

MBS, Chapter 11                                 Exercises: 11.62, 11.116

 

Multiple regression       
Date: Tu 10/18/11

11.9 Comparing Nested Models model.   

MBS, Chapter 11                                 Exercises: 11.103

 

Multiple regression       
Date: Th 10/20/11

Review

 

Handout
assignment II

Final Exam             
Date: Th 10/20/11

                                                                   

 

 

 

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.

Full version of Minitab 16:

There are several ways to get Minitab 16

1.     Purchase the full version from the computer store at an academic price of $115.

2.     Rent the full version program for $30 for six months or for $50 for twelve months from www.e-academy.com/minitab.

3.     Use the full version program for no charge through the Stern CITRIX system.

CITRIX is found at http://apps.stern.nyu.edu.  CITRIX permits you to run an online version of MINITAB 16 (as well as other software).  Connection difficulties are not uncommon; Stern’s Information Technology group (helpdesk@stern.nyu.edu) can help if you have connection difficulties.  I found that Firefox is the least troublesome browser to use when accessing Minitab via CITRIX.

You can save your work to your local computer by selecting in the save dialog “My Computer” then “C$ on ‘Client’ (V:)”.

Excel also has a number of statistical functions.  I recommend that you avoid this program for statistical applications.  While Excel’s statistical work is generally correct, there are a number of annoying errors, and the program lacks the flexibility of a full-featured statistics package.

Course work will involve instances of simple calculations (+, -, x, ÷, memory, and square root), and for these a hand-held calculator is helpful but not necessary or required.  

 

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                               20%

 

Grading

At NYU Stern we seek to teach challenging courses that allow students to demonstrate their mastery of the subject matter.  In general, students in undergraduate core courses can expect a grading distribution where: 

Note that while the School uses these ranges as a guide, the actual distribution for this course and your own grade will depend upon how well you actually perform in this course.

 

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.

 

Professional Responsibilities For This Course

Attendance

Attending class, arriving to class on time and staying to the end of the class period are essential to your success in this course and affect your grade.  Absences may be excused only in the case of serious illness, grave family emergencies, religious observance, or civic obligation and must be documented.  If you will miss a class for religious observance or civic obligation, you must notify me no later than the first week of class.  Job interviews and incompatible travel plans are considered unexcused absences.

Participation

In-class contribution is a significant part of your grade and an important part of our shared learning experience. Your active participation helps me to evaluate your overall performance.
You can excel in this area if you come to class on time and contribute to the course by:

Assignments and Make-up Policy

No make-up exams will be given and late assignments will not be accepted unless you had a documented serious illness or family emergency. Exceptions to this policy for reasons of religious observance or civic obligation will only be made available when the assignment cannot reasonably be completed prior to the due date and you make arrangements for late submission in advance.

Classroom Norms

Laptops, cell phones, Smart-phones and other electronic devices must be turned off prior to the start of class. 

Exception:  Laptops may be used for in-class hands-on assignments.

 

Stern Policies

Collaboration on Graded Assignments
Students may choose to work together in groups of two on homework assignments.  Each group will hand in ONE assignment with both names on the document. 

 

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.

 

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. 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.

 

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. 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.

 

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. 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.

 

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