Term : Spring 2015
Course/CRN/Section : MGT 2120/25307/5
Title
Credit
Schedule
: Statistical Methods for Business II
: 3 hours
: 1:40 to 2:55 p.m. T, Location: Fletcher 316/Online hybrid
Instructor
Office Location
Office Phone
Office Hours
Email Address
PREREQUISITES
: Parthasarati Dileepan, Ph.D.
: Fletcher Hall 106
: (865) 315-8280; Campus: 423-425-4675;
: On campus: 12:00 – 1:30 p.m. TR; Online: 2:00 – 3:00 p.m. MW
: Dileepan@mocs.utc.edu
MGT 1000 or CPSC 1000, MGT 2110 or MATH 2100 with a minimum grade of C, and Math ACT score of
26 or above or MATH 1130 or MATH 1710 with a minimum grade of C or MATH 1720 or MATH 1830 or
MATH 1910, or department head approval.
COURSE DESCRIPTION
Advanced concepts of statistical inference including hypothesis testing for two populations, contingency, tables, goodness of fit, analysis of variance, and simple and multiple regression analysis.
Emphasis is on computer solutions of business statistical applications. Differential Course Fee will be assessed
COURSE LEARNING OUTCOMES

Develop practical skills for statistical estimation and inference, ANOVA, and Regression Analysis, for business decision making. Build strong proficiency in the use of computer spreadsheet for statistical data analysis. Specifically, students will develop expertise in using Excel software for the following statistical analyses.

Data analysis – summarization and presentation

Develop confidence intervals and perform hypothesis testing

Perform ANOVA (Single factor, Block design, and factorial design)

Perform regression analysis including testing for significance and developing confidence and prediction intervals

Develop regression models using step-wise regression technique

Logit regression
TEXT
General MindLink for MindTap Business Statistics Instant Access for
Anderson/Sweeney/Williams/Camm/Cochran's Statistics for Business & Economics, 12th Edition
AUTHORS: Anderson/Sweeney/Williams/Camm/Cochran - ©2014
ISBN10: 1-285-58727-8
ISBN13: 978-1-285-58727-1

COURSE CONDUCT
The content of the course will be delivered online through the Blackboard. A learning module for each chapter will be made available in Blackboard. The learning module will contain all the necessary materials for mastering the content of the chapter. These materials include, but not limited to:

Powerpoint notes

Audio/video files presenting content

Video files describing how to solve the class example problems, and

Any other material that may be appropriate
BLACKBOARD
MGT 2120 Blackboard link
All the class materials including class notes, lectures, discussions, homework, quiz, exam, etc., will be made available in Blackboard. There will be one learning module folder for each chapter. The learning module will contain all the necessary materials for mastering the content of the chapter. These materials include, but not limited to:

Powerpoint notes

Audio/video files presenting content

MS-Word document containing example class problems
There will also be a course schedule section. In this section I will have one folder for each week. This folder will contain a list of tasks to complete for each class. This list of tasks will include, but not limited to:

Reading assignment

Learning module content to view and complete

Homework assignment to submit, and

Quizzes to complete
New content will be added to Blackboard on a regular basis. Students must check Blackboard at least twice a day and be aware of these additions as soon as they are made.
EVALUATION/ASSESSMENT
Two Exams
Chapter Tests
Homework
Total
MindTap
MindTap
Blackboard
200
150
150
500
40%
30%
30%
100%
EXAMS
Exams are open book and open notes. Exams will be administered as follows:
Exam 1 February 24, 2015 (Tuesday)
Exam 2 April 28, 2015 (Tuesday)
MindTap
MindTap
CHAPTER TESTS
Tests on every chapter covered will be administered using the MindTap platform. The tests will cover theoretical concepts as well as numerical problems. Students are encouraged to use Excel for completing the tests.
HOMEWORK

All homework must be done in Excel spreadsheet

Homework must be submitted in Blackboard, emailed homework will NOT be graded

LATE POLICY FOR HOMEWORK/QUIZ

No late homework/test will be allowed more than three weekdays after it was due.

The first two late homework/test completions within three weekdays will be accepted without any penalty.

After the first two late homework/test, 5% per day penalty per day (including weekends) will be assessed for the third to fifth late homework/test completions.

No late homework/test will be accepted after the fifth late submission/completion.
GRADING SCALE
A: Average > 90%; B: Below 90% but > 80%; C: Below 80% but > 70%; D: Below 70% but > 60%; F:
Average < 60%
TECHNOLOGY PREREQUISITE

High speed internet

Excel 2010 or later with Data Analysis (Mac users can use StatPlus:mac LE – a free edition of
StatPlus:mac Professional developed by AnalystSoft, available for download at this link: http://www.analystsoft.com/en/products/statplusmacle/

Familiarity with Google Plus Hangouts
This is an online course. All course materials and homework will be made available online via
Blackboard. Therefore, students must have access to high-speed internet. Not having adequately fast internet will not be accepted as a legitimate excuse for completing or submitting any requirements late.
Office hours will be offered both in my office and online. Familiarity with online chat services like
Google Plus Hangouts for office hours help is required. The UTC Mocs email account comes with Google
Plus account as well. It is the student’s responsibility to get trained in the use of Google Plus Hangouts.
COMMUNICATION
The primary means of communication is via email. To enhance student services, the University uses your UTC email address for all communications. Please check your UTC email on a regular basis at least twice a day. If you have problems with accessing your UTC email account, contact the Call Center at
423/425-4000. In addition, you may use (865) 315-8280 to contact me by phone and leave a message.
In either of these cases you can expect a response within 24 hours. My campus phone number is 423-
425-4675. Responses to messages left in this number may take longer.
ACCOMMODATION STATEMENT
If you are a student with a disability (e.g. physical, learning, psychiatric, vision, hearing, etc.) and think that you might need special assistance or a special accommodation in this class or any other class, call the Disability Resource Center (DRC) at 425-4006 or come by the office, 102 Frist Hall.
COUNSELING CENTER STATEMENT
If you find that personal problems, career indecision, study and time management difficulties, etc. are adversely impacting your successful progress at UTC, please contact the Counseling and Career Planning
Center at 425-4438.

HONOR CODE PLEDGE (from the UTC Student Handbook)
I pledge that I will neither give nor receive unauthorized aid on any test or assignment. I understand that plagiarism constitutes a serious instance of unauthorized aid. I further pledge that I exert every effort to insure that the Honor Code is upheld by others and that I will actively support the establishment and continuance of a campus-wide climate of honor and integrity.
Tentative schedule (subject to change)
Week
Week 1
Week 2
Week 3
Week 4
Week 5
Date Chapter Topic
1/6/2015 Chapters 1, 2 Data and statistics
Descriptive Statistics: Tabular and Graphical displays
1/13/2015 Chapters 3, 6, 7 Descriptive statistics: Numerical measures,
Normal Probability distribution
Sampling distribution
1/20/2015 Chapters 8, 9 Interval estimation
Hypothesis testing
1/27/2015 Chapter 10 Inference about two populations
2/3/2015 Chapter 10 Inference about two populations
Week 6
Week 7
2/10/2015 Chapter 11
2/17/2015 Chapter 12
2/24/2015 Exam 1
Week 8 2/24/2015 Chapter 13
Inference about two population variances
Test of independence and Goodness of Fit test
Week 9 3/3/2015 Chapter 13
3/8/2015 Last day to drop
Analysis of Variance
3/10/2015 Spring Break -- no class
Week 10 3/17/2015 Chapter 14 Analysis of Variance
Week 11 3/24/2015 Chapter 14 Simple Regression Analysis
Week 12
Week 13
Week 14
3/31/2015
4/7/2015
4/14/2015
4/28/2015 Exam 2
Chapter 15
Chapter 15
Chapter 16
Simple Regression Analysis
Multiple Regression Analysis
Regression Analysis: Model Building
Important Dates
February 24, 2015 (Tuesday)
March 8, 2015 (Sunday)
March 10, 2015
April 14, 2015 (Tuesday)
: Exam 1
: Last day to drop with a W
: Spring Break (No class)
: Last class
April 28, 2015 (Thursday) : Exam 2
Exam dates are tentative only. Changes, if become necessary, will be announced by email.

Topics covered
Review of MGT 2110 topics:
Chapter 1:
§1.2 Data
§1.3 Data Sources
§1.4 Descriptive Statistics
§1.5 Statistical Inference
§1.6 Computers and Statistical Analysis
Chapter 2:
§ 2.1 Summarizing Categorical Data
§ 2.2 Summarizing Quantitative Data
§ 2.3 Summarizing Data for Two Variables using Tables
§ 2.4 Summarizing Data for Two Variables using Graphical Displays
Chapter 3:
§3.1 Measures of Location
§3.2 Measures of Variability
§3.3 Measures of Distribution
§3.4 Five Number Summary and box Plots
§3.5 Measures of Association Between Two Variables
Chapter 5: Discrete Probability
§5.1 Random Variables
Chapter 6: Continuous Probability Distributions
§6.2 Normal Probability Distribution
Chapter 7: Sampling and Sampling Distributions
§7.4 Introduction to Sampling Distribution
§7.5 Sampling Distribution of 𝑥̅
§7.6 Sampling Distribution of 𝑝̅
Chapter 8: Interval Estimation
§8.2 Population Mean: 
unknown
§8.4 Population Proportion
Chapter 9: Hypothesis tests
§9.1 Developing null and alternative hypotheses
§9.2 Type I and Type II Errors
§9.4 Population Mean: s unknown
§9.5 Population Proportion
MGT 2120 topics
Chapter 10: Inference about means and proportions with two populations
§10.1 Inference about the difference between two population means: 
§10.2 Inference about the difference between two population means: 
1
1
and

and

2
2
known
unknown

§10.3 Inference about the difference between two population means: Matched samples
§10.4 Inference about the difference between two population proportions
Chapter 11: Inferences about population variances
§11.1 Inferences about a population variance
§11.2 Inferences about two population variances
Chapter 12: Comparing multiple proportions, tests of independence and goodness of fit
§12.1 Goodness of Fit: A Multinomial Population
§12.2 Test of independence
§12.3 Goodness of fit test
Chapter 13: Experimental design and Analysis of variance
§13.1 An introduction to experimental design and Analysis of variance
§13.2 Analysis of variance and the completely randomized design
§13.3 Multiple comparison procedures
§13.4 Randomized block design
§13.5 Factorial experiment
Chapter 14: Simple Linear Regression
§14.1 Simple linear regression model
§14.2 Least squares method
§14.3 Coefficient of determination
§14.4 Model assumptions
§14.5 Testing for significance
§14.6 Using the estimated regression equation for estimation and prediction
§14.7 Computer solution
§14.8 Residual analysis: Validating model assumptions
§14.9 Residual analysis: Outliers and influential observations
Chapter 15 Multiple Regression
§15.1 Multiple regression model
§15.2 Least squares method
§15.3 Multiple coefficient of determination
§15.4 Model assumptions
§15.5 Testing for significance
§15.6 Using the estimated regression equation for estimation and prediction
§15.7 Categorical independent variables
§15.8 Residual analysis
§15.9 Logistic regression
Chapter 16: Regression analysis: Model building
§16.1 General linear model
§16.2 Determining when to add or delete variables
§16.3 Analysis of a larger problem
§16.4 Variable selection procedures
§16.5 Multiple regression approach to experimental design
§16.6 Autocorrelation and the Durbin-Watson test