NYU Stern School of Business

Undergraduate College

STAT-UB.0103.001 (C22.0103): STATS F/BUS CNTL REGRESS & FORECASTING MODELS

Fall 2012

Instructor Details

Giloni, Avi

agiloni@stern.nyu.edu

TBA

8-171 KMC

 

Course Meetings

MTR, 8:00am to 9:15am

Tisch T-LC25


 

Final Exam:

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

 

Course Description and Learning Goals

See Syllabus section below.

 

Course Outline

See Syllabus section below.

 

Required Course Materials

See Syllabus section below.

 

Assessment Components

.

 

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.

 

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

 
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

 

Classroom Norms

 

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.

 

Syllabus Information

Course Outline – Fall 2012

STAT-UB.0103.01 - Statistics for Business Control and Regression Models


 

Class meets:  Monday, Tuesday, & Thursday, 8:00 AM - 9:15 AM

Instructor:  Avi Giloni

Office:  8-171 KMC

Telephone:  212-998-0825

E-mail:  agiloni@stern.nyu.edu

Classroom:  LC-25 Tisch Hall

Office hours:  Monday, 9:30 AM - 10:30 AM,  Tuesday & Thursday, 9:30 AM - 10:00 AM

Course Objectves:

The basic objective of this course is to provide the business student with a strong fundamental understanding of statistics and its applications. Students will learn statistical applications utilizing real world examples and exercises from various fields. This course will survey the topics of descriptive statistics, inferential statistics, linear regression and their applications. 

 

Course Organization:

 

The course lectures, handouts, and homework assignments are the materials that you will be held responsible for. The lectures will follow the lecture notes/slides that will be handed out and are on Blackboard. However, the lectures will often contain more information than what is on the slides. The textbook should be considered as supplementary reading.

We will use Minitab, Release 15/16, for data analysis. A student version of this software is included with the textbook by the NYU bookstore. Minitab 15/16 will be available in the computer labs. The differences between Minitab 15/16 and the student version are minor. You can also rent Minitab 15/16 for a fixed time period (a certain number of months) from http://www.onthehub.com/minitab/.

The course materials can be found on the Blackboard site for this course. This will be the primary way that we will correspond with each other outside the classroom. However, I will be available for Office Hours as well. There is also an optional Internet site with study aids.

 

Required Text(s) and Materials:

 

1.              McClave, Benson, and Sincich, Statistics for Business and Economics, Second Custom Edition for New York University, Prentice ­Hall, (REQUIRED).

2.              Minitab 15/16 or  Minitab student version bundled with text book (REQUIRED)

3.              Blackboard Course Site (REQUIRED).

4.              Boudreau, Student’s Solutions Manual, Prentice-Hall (RECOMMENDED).

 

 

Grading Policy:

 

We will have homework, two midterms, a final exam, and a project. Your grade will be based on these, as well as class participation.

 

Midterm 1                   25%

Midterm 2                   25%

Homework                  10%

Project                         10%

Final                            30%

 

Homework:

Homework counts for 10% of your grade. The assignments must be completed and handed in on time. Late homework will not be collected. Students are expected to come to class prepared having read text and assigned readings prior to class. It is suggested that students keep a copy of their homework to study from (in case it is not returned before an exam).

Project:

There will be a project, which counts for 10% of the grade. In the project, you will analyze a data set of your choice, using methods you have learned in the course. The project is a group project. Groups must be at least two students and no more than four students. The project will be broken down into short modules, spread over the entire semester. For each module, the group should submit just one report, with all names on it. Modules handed in late will not be accepted. When each module is handed in, the previous modules should be attached, but these will not be re-graded. More details on the project are available on the Blackboard course site.

              Late Assignments and Make-up Policy:

At the discretion of the professor, late assignments will either not be accepted or will incur a grade penalty unless due to documented serious illness or family emergency.  Professors will make exceptions for religious observance or civic obligation only when the assignment cannot reasonably be completed prior to the due date and the student makes arrangements for late submission with the professor in advance.

 

Class Attendance And Participation:

 

Class attendance is mandatory and part of a student’s grade.  Absences may be excused only in the case of documented serious illness, family emergency, religious observance, or civic obligation.  If you will miss class for religious observance or civic obligation, you must inform your instructor no later than the first week of class.  Recruiting activities are not acceptable reasons for class absence.

 

Students are expected to arrive to class on time and stay to the end of the class period.  Chronically arriving late or leaving class early will have an impact on a student’s grade. Students may enter class late only if given permission by the instructor and can do so without disrupting the class.  Note: Instructors are not obligated to admit late students or may choose to admit them only at specific times and instructors are not obligated to readmit students who leave class.

 

Participation is an essential part of learning in this course.  Students are expected to participate in all facets of classroom learning. I expect you to take an active role in learning Statistics. I may call on you, and I want you to ask questions. There's no such thing as a "bad" question or comment, so don't be afraid to speak up (in an orderly fashion). This helps me to identify points that I need to explain further. If you demonstrate that you are actively and consistently participating and involving yourself in the learning process (this obviously includes attending class), I may boost your final grade by up to one point, for example, from a B+ to an A-.

 

 

Seating:

 

Please select a seat that you will keep for the entire semester. At the beginning of the fifth class meeting, please give me an index card with your photo attached, giving your name, seat location, class, and any other information you would like to provide. This helps me in getting to know you, in keeping track of attendance, and in giving credit for class participation.

 

 

Classroom Norms:

 

Cell phones, smartphones and similar electronic devices are a disturbance to both students and professors.  All such electronic devices must be turned off prior to the start of each class meeting.

 

Ethical Guidelines: Student Code of Conduct:

 

All students are expected to follow the Stern Code of Conduct

http://www.stern.nyu.edu/uc/codeofconduct. A student’s responsibilities include, but are not limited to, the following:

 

A duty to acknowledge the work and efforts of others when submitting work as one’s own.  Ideas, data, direct quotations, paraphrasing, creative expression, or any other incorporation of the work of others must be clearly referenced.

A duty to exercise the utmost integrity when preparing for and completing examinations, including an obligation to report any observed violations.

Students with Disabilities:

Students whose class performance may be affected due to a disability should notify the professor immediately so that arrangements can be made in consultation with the Henry and Lucy Moses Center for Students with Disabilities http://www.nyu.edu/csd/ to accommodate their needs.

 

Tentative Schedule of Topics - Fall 2012

Topic #

Topic Description

Chapter

Topic 1

Introduction to Statistics, Types of Data, Collecting Data, Populations and Samples

Chapter 1, Handout 1

Topic 2

Tables, Charts and Graphs for Categorical and Numerical Data, Measures of Central Tendency, Variation and Shape

Chapter 2, Handout 1

Topic 3

Introduction to Probability

Chapter 3, Handout 2

Topic 4

Discrete Probability Distributions

Chapter 4, Handout 3

Topic 5

Continuous Probability Distributions

Chapter 4, Handout 4

Topic 6

Sampling Distributions and the Central Limit Theorem

Chapter 4,   Handout 4

Topic 7

Confidence Intervals and Sample Size Determination

Chapter 5, Handout 5

Topic 8

Hypothesis Tests

Chapter 6, Handout 6

Topic 9

Simple Linear Regression

Chapter 10, Handout 7

Topic 10

Multiple Regression

Chapter 11, Handout 8

Topic 11

Inferences based on Two Samples

Chapter 7, Handout 6

 

 

Tentative Calendar - Fall 2012

 

Date

Topic Covered

Assignment

09/04/12

1

Read Chapter 1 and Handout 1

09/06/12

1,2

                            

09/10/12

2

Read Chapter 2

09/11/12

2

Submit Hmwk 1

09/13/12

2,3

 

09/17/12

3

Read Chapter 3 and Handout 2

09/18/12

3

Submit Hmwk 2

09/20/12

3,4

 

09/24/12

4

Read Chapter 4 and Handout 3

09/25/12

4

Submit Hmwk 3

09/27/12

4

 

10/01/12

4,5

 

10/02/12

5

 

10/04/12

5

Submit Hmwk 4

10/08/12

5,6

 

10/09/12

Midterm 1 (Topics 1-4, 5)

 

10/11/12

6

Submit Module 1

10/15/12

No Class

 

10/16/12

No Class

 

10/18/12

6

Submit Hmwk 5

10/22/12

6

 

10/23/12

7

Read Chapter 5 and Handout 5

10/25/12

7

Submit Hmwk 6

10/29/12

7

 

10/30/12

7

 

11/01/12

8

Read Chapter 6 and Handout 6

11/05/12

8

Submit Hmwk 7

11/06/12

8

 

11/08/12

8

 

11/12/12

9

Read Chapter 10 and Handout 7

11/13/12

9

Submit Hmwk 8

11/15/12

Midterm 2 ( Topics 5 - 8)

 

11/19/12

9

 

11/20/12

9

Submit Module 2

11/22/12

No Class

 

11/26/12

9

 

11/27/12

9

 

11/29/12

9

 

12/03/12

10

Read Chapter 11 and Handout 8

12/04/12

10

Submit Hmwk 9

12/06/12

10

 

12/10/12

10

 

12/11/12

10

 

12/12/12

10,11

Read Chapter 7

12/13/12

11

Submit Hmwk 10 and Module 3

12/20/12

Final Exam (Cumulative, but focused on topics 9 – 11)

 

 

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