# Syllabus

```BUAD 310 – Applied Business Statistics
Syllabus – Spring 2015
Instructor:
Office:
Dr. Xin Tong
HOH504
Class:
Office Hours:
HOH EDI
MW 3:20-4:20 PM
Email:
[email protected]
TA office hours: Thursday 12pm-4pm BRI 401
Course Description
In this course, we will focus on learning various statistical techniques and their applications that
will assist you in making business decisions. The primary objective of this course is to enable
students to perform and understand statistical analysis of data, with the view of being able to
critically evaluate statistical reports or findings. You will learn to think critically about how
statistics is used in business and how it impacts your day-to-day life and career. No mathematical
background beyond high school algebra is required for an understanding of the material.
Course Learning Objectives
You will explore and describe data, examine sampling distributions, make estimations, test
hypotheses, perform simple and multiple regression analysis, and build models using extensive
software applications both independently and collaboratively.
These applications will guide you to:
1. Describe the concepts of descriptive statistics and infer summary analyses about the
sample and measure;
2. Recognize different models of statistical processes such as hypothesis testing through
Chi-square, linear and multiple regression, etc.;
3. Explain statistical processes and choose which process to use for particular data
analysis applications;
4. Learn to interpret statistical results as a basis for decision-making;
5. Learn to use applicable statistics software;
7. Communicate your interpretation of the results of statistical analysis logically and
persuasively in speaking and writing.
These course level objectives support the six Marshall Program Learning Goals to varying degrees.
Details may be found in the Appendix of this syllabus.
Required Materials
1. The course textbook USC Statistics for Business: Decision Making and Analysis (3rd
Edition) by Robert Stine and Dean Foster, Pearson, 2014, is available at the bookstore.
You are not required to purchase a hard copy of the textbook. You will automatically
have access to the electronic version of the textbook after you register with MyStatLab,
which is a website provided by the publisher. Registration instructions are given on page 5
below.
2. Each student has to register with MyStatLab to have access to the homework, which
will be administered online. Registration with MyStatLab requires an access code, which
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you can either purchase online, or get automatically when you buy a new textbook at the
USC bookstore. More details are provided on page 5 below.
Prerequisites and/or Recommended Preparation:
No mathematical background beyond high school algebra is required.
Course Notes:
The slides for the course will be available through the LectureTools website. Other handouts will
be posted on your BUAD 310 Blackboard. If you would like hard copies of the slides, it will be
class preparation materials or instructions.
Software:
Lecture sessions utilize interactive LectureTools technology. To participate in class, register using
the link provided on the course BlackBoard page. Application sessions utilize Excel 2010 or 2013
software and the Excel Data Analysis Pack free add-on. Students are required to bring a laptop with
Microsoft Excel software installed to all applications sessions, unless instructed otherwise..
Lecture:
Mid-Term Exam (Part I)
Homework Assignments
20%
15%
Application:
Mid-Term Exam (Part II)
Application Exercises
8%
20%+2%
(peer review)
Final Exam
35%
TOTAL
100%
calculate your overall score for the class. Class participation during the lectures, including using
the LectureTools software, may increase your overall score by a bonus of up to 1%.
Class Attendance & Participation:
You are expected to attend all classes. In addition to expanded explanation and examples of
important statistical analysis concepts, it also gives you the opportunity to pose questions.
The applications sections of the class constitute 30% of the course grade. To earn full credit
requires not only attendance, but also active contribution to every application exercise. The lowest
application exercise grade that you earn will be dropped.
I have no problem going over a concept multiple times. If you feel uneasy bringing up your
questions in class, take advantage of the many opportunities to speak with me one-on-one. I am
always accessible by e-mail, and will be more than happy to speak with you before or after class or
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during office hours. Note: if your question requires a conversation rather than a short answer,
email is not the best way to go – please talk to me after class or during office hours, and I will be
Homework:
You will view your assignments and submit the answers online, using www.mystatlab.com.
There will be about seven HW assignments, and your lowest HW score will be dropped. Due dates
will be specified for each HW assignment. Late assignments will not be accepted.
Application Exercises:
You will use statistical software for data-analysis and problem solving. You will work in teams that
will be assigned by your application session professor and need to present a coherent team report.
The exercises are constructed in order to lead you through key topics introduced in lectures and
as observed by your application session professor and your peers. Teams will be assigned and will
provide the opportunity to practice the professional collaboration required by employers. There are
no make up session for any missed applied session. You must attend only your designated session.
Midterm test and Final Exam:
The midterm exam will consist of two parts. Part (I) will be given in lecture on the date announced
in the course schedule (page 6). You may bring a single handwritten sheet (both sides) containing
formulas to the midterm and you will be allowed two handwritten sheets (both sides) for the final
exam. Part (II) of the midterm exam will be given in application sessions the same week as the
lecture exam. No make-ups of tests will be given. You will receive a grade of zero for each
missed test unless you have a written excuse from your doctor or the University.
The final examination will take place on Wednesday, May 6, 2015, 8:00-10:00am for all
BUAD310 sessions. Note that it is an exception final, as it does not take place at the regularly
listed time. The final exam is comprehensive (this is inevitable in a Statistics course) but greater
emphasis will be given to the material taught later in the semester. You cannot be exempted from
this final under any circumstances. The final exam will NOT be given at any other time.
According to the USC Office of Academic Records and Registrar, “No student in a course with a
final examination is permitted to omit the final examination or take the final examination prior to
its scheduled date, and no instructor is authorized to permit a student to do so. No student is
allowed to re-take a final examination or do extra work in a course after the semester has ended
for purposes of improving his or her grade.”
Collaboration Policy:
Discussion of homework problems is permitted and encouraged; however, each student is required
to prepare and submit his or her solutions, including computer work, independently.
Collaboration of any sort on tests and exams is prohibited and will result in a 0 on that exam.
I reserve the right to bring any potential cheating issues to the administration for further penalties.
MARSHALL GUIDELINES
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The last day to register and add classes is Friday, January 30. The last day to drop a class without a
mark of “W” is also January 30. For more information, visit https://classes.usc.edu/term20151/calendar/
Statement for Students with Disabilities
Any student requesting academic accommodations based on a disability is required to register with
Disability Services and Programs (DSP) each semester. A letter of verification for approved
accommodations can be obtained from DSP. Please be sure the letter is delivered to me as early in
the semester as possible. DSP is located in STU 301 and is open 8:30 a.m.–5:00 p.m., Monday
through Friday. The phone number for DSP is (213) 740-0776. For more information visit
www.usc.edu/disability .
USC seeks to maintain an optimal learning environment. General principles of academic honesty
include the concept of respect for the intellectual property of others, the expectation that individual
work will be submitted unless otherwise allowed by an instructor, and the obligations both to
protect one’s own academic work from misuse by others as well as to avoid using another’s work
as one’s own. All students are expected to understand and abide by these principles. SCampus, the
Student Guidebook, (www.usc.edu/scampus or http://scampus.usc.edu) contains the University
Student Conduct Code (see University Governance, Section 11.00), while the recommended
sanctions are located in Appendix A.
Students will be referred to the Office of Student Judicial Affairs and Community Standards for
further review, should there be any suspicion of academic dishonesty. The Review process can be
standards set forth by these guidelines and our programs will not be tolerated by the USC Marshall
community and can lead to dismissal.
Class Notes Policy
Notes or recordings made by students based on a university class or lecture may only be made for
purposes of individual or group study, or for other non-commercial purposes that reasonably arise
from the student’s membership in the class or attendance at the university. This restriction also
applies to any information distributed, disseminated or in any way displayed for use in relationship
to the class, whether obtained in class, via email or otherwise on the Internet, or via any other
medium. Actions in violation of this policy constitute a violation of the Student Conduct Code, and
may subject an individual or entity to university discipline and/or legal proceedings.
Emergency Preparedness/Course Continuity
In case of a declared emergency if travel to campus is not feasible, USC executive leadership will
announce an electronic way for instructors to teach students in their residence halls or homes using
a combination of Blackboard, teleconferencing, and other technologies.
MyStatLab
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MyStatLab is an interactive website where you can:
 Self-test & work through practice exercises with step-by-step help to improve your math skills.
 Study more efficiently with a personalized study plan and exercises that match your book.
 Get help when YOU need it. MyStatLab includes multimedia learning aids, videos, animations,
and live tutorial help.
Before You Begin:
To register for MyStatLab, you need:
 A MyStatLab student access code (packaged with your new text, standalone at your
bookstore, or available for purchase with a major credit card at www.pearsonmylab.com)
 Your instructors’ Course ID: tong23586
Student Registration:
 Under Register, click Student.
information appears on the next page. If it does not look correct, contact your instructor to verify the
Course ID.
possible,
Policy.
 Click Access Code. Enter your Access Code in the boxes and click Next. If you do not
have an access code and want to pay by credit card or PayPal, select the access level you want and
follow the instructions. You can also get temporary access without payment for 14 days..
Once your registration is complete, a Confirmation page appears. You will also receive this
information by email. Make sure you print the Confirmation page as your receipt. Remember to
Signing In:
 On the left, click the name of your course.
The first time you enter your course from your own computer and anytime you use a new
computer, click the Installation Wizard or Browser Check on the Announcements page. After
Need help?
Contact Product Support at http://www.mystatlab.com/student-support for live CHAT, email, or phone
support.
Lecture Tools
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Lecture Tools software will be used in the lecture section of this course. Lecture Tools allows you
to save the PowerPoints from each class that you attend, pose questions anonymously in real time
Lecture Tools during each class meeting. Instructions for registering with Lecture Tools are posted
on the course BlackBoard page. Lecture Tools may be accessed using a laptop or smart phone.
TENTATIVE COURSE SCHEDULE – BUAD 310
(Test dates are set, but topics and homework due dates may be modified.)
Week Date
1
1/12
1/14
2
1/19
1/21
3
1/26
1/28
4
2/2
2/4
5
2/9
2/11
6
2/16
2/18
7
2/23
2/25
8
3/2
3/4
9
3/9
3/11
11
3/16 –
3/21
3/23
3/25
12
3/30
4/1
13
4/6
10
Topics
Introduction
Descriptive Statistics
Application Exercise
Martin Luther King Day, university holiday
Descriptive Statistics
Application Exercise
Probability: Basic Concepts
Random Variables
Application Exercise
Normal Distribution
Normal Distribution
Application Exercise
Sampling Distributions
Sampling Distributions
Application Exercise
Presidents’ Day, university holiday
Confidence Intervals
Application Exercise
Hypothesis Testing
Hypothesis Testing
Application Exercise – Statistical tests
Chi-Square Tests
Chi-Square Tests
Application Exercise
Midterm Review
Midterm Exam
Application Midterm Exam (Part II)
Book Chapters
[Stine & Foster]
Chapters 1, 2
Chapters 3, 4
Due Dates
Chapters 5, 6
Chapters 7, 8
Chapter 9
Homework #1
Chapter 11
Chapter 11
Homework #2
Chapters 12, 13
Chapters 12, 13
Chapter 14
Chapter 14
Homework #3
Chapter 15
Chapters 15, 16
Chapters 17, 5
Chapters 17, 5
Homework #4
Spring break
Simple Linear Regression
Simple Linear Regression
Application Exercise
Simple Linear Regression
Simple Linear Regression
Application Exercise
Multiple Regression
Chapters 18-21
Chapters 18-21
Chapters 18-21
Chapters 18-21
Homework #5
Chapter 22
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4/8
4/13
4/15
14
4/20
15
4/22
4/27
4/29
16
Multiple Regression
Application Exercise
Multiple Regression
Multiple Regression
Application Exercise
Multiple Regression, Categorical Explanatory
Variables
Multiple Regression, Categorical Explanatory
Variables
Application Exercise
Multiple Regression, Variable Selection
Review for the Final
Active student-led review
Chapter 22
Chapter 22
Chapter 22
Homework #6
Chapter 24
Chapter 23
Homework #7
Wednesday, May
6th
Final Exam
8:00-10:00AM
APPENDIX
Marshall’s Six Undergraduate Program Learning Goals
#
1
1.1
1.2
Marshall Program Learning Goal
Description
types of markets and key business
areas and their interaction to
effectively manage different types
of enterprises.
Specifically, students will:
Demonstrate foundational
Degree of
Emphasis
Low
BUAD310 Course Objectives that Support This
BUAD310 Course Objectives 1-7 support Goal 1
1. Understand the concepts of descriptive statistics,
inference, summarizing, and sampling
2.Recognize different models of statistical processes
3.Explain statistical processes and choose which to
use for particular data analysis applications
4.Learn to interpret statistical results as a basis for
decision-making;
5.Learn to use applicable statistics software;
6.Collaborate effectively to use statistical analysis to
7.Communicate results of statistical analysis
logically and persuasively
1. Understand the concepts of descriptive statistics,
inference, summarizing, and sampling
4.Learn to interpret statistical results as a basis for
decision-making;
6.Collaborate effectively to use statistical analysis to
Understand the interrelationships
between functional areas of
business so as to develop a general
management.
-7-
1.3
Apply theories, models, and
frameworks to analyze relevant
markets (e.g. product, capital,
commodity, and factor and labor
markets).
1.4
Show the ability to utilize
databases, software) relevant to
will understand how local,
regional, and international
markets, and economic, social
and cultural issues impact
anticipate new opportunities in any
marketplace. Specifically, students
will:
Understand how local, regional and
global markets interact and are
impacted by economic, social and
cultural factors.
Understand that stakeholders,
environments (legal, regulatory,
vary across regions of the world.
critical thinking skills so as to
become future-oriented decision
makers, problem solvers and
innovators. Specifically, students
will:
Understand the concepts of critical
thinking, entrepreneurial thinking
and creative thinking as drivers of
innovative ideas.
2
2.1
2.2
3
3.1
7.Communicate results of statistical analysis
logically and persuasively
1. Understand the concepts of descriptive statistics,
inference, summarizing, and sampling
2.Recognize different models of statistical processes
3.Explain statistical processes and choose which to
use for particular data analysis applications
4.Learn to interpret statistical results as a basis for
decision-making;
5.Learn to use applicable statistics software
6.Collaborate effectively to use statistical analysis to
7.Communicate results of statistical analysis
logically and persuasively
5.Learn to use applicable statistics software;
6.Collaborate effectively to use statistical analysis to
Low
BUAD310 Course Objectives 6-7 support Goal 2
6.Collaborate effectively to use statistical analysis to
6.Collaborate effectively to use statistical analysis to
7.Communicate results of statistical analysis
logically and persuasively
High
BUAD310 Course Objectives 1-7 support Goal 3
3.Explain statistical processes and choose which to
use for particular data analysis applications
4.Learn to interpret statistical results as a basis for
decision-making;
6.Collaborate effectively to use statistical analysis to
7.Communicate results of statistical analysis
logically and persuasively
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3.2
3.3
3.4
4
4.1
4.2
4.3
Critically analyze concepts, theories
and processes by stating them in
their own words, understanding key
components, identifying
assumptions, indicating how they
are similar to and different from
others and translating them to the
real world.
Be effective at gathering, storing,
and using qualitative and
quantitative data and at using
analytical tools and frameworks to
problems.
Demonstrate the ability to
anticipate, identify and solve
able to identify and assess central
problems, identify and evaluate
potential solutions, and translate a
chosen solution to an
implementation plan that considers
future contingencies
promote their effectiveness as
Specifically, students will:
Recognize, understand, and analyze
the motivations and behaviors of
stakeholders inside and outside
organizations (e.g., teams,
departments, consumers, investors,
auditors).
Recognize, understand and analyze
the roles, responsibilities and
behaviors of effective managers and
e.g., marketing, finance,
accounting.
3.Explain statistical processes and choose which to
use for particular data analysis applications
4.Learn to interpret statistical results as a basis for
decision-making;
6.Collaborate effectively to use statistical analysis to
7.Communicate results of statistical analysis
logically and persuasively
1. Understand the concepts of descriptive statistics,
inference, summarizing, and sampling
2.Recognize different models of statistical processes
3.Explain statistical processes and choose which to
use for particular data analysis applications
4.Learn to interpret statistical results as a basis for
decision-making;
5.Learn to use applicable statistics software;
6.Collaborate effectively to use statistical analysis to
7.Communicate results of statistical analysis
logically and persuasively
6.Collaborate effectively to use statistical analysis to
7.Communicate results of statistical analysis
logically and persuasively
Low
.
Goal 4
6.Collaborate effectively to use statistical analysis to
7.Communicate results of statistical analysis
logically and persuasively
3.Explain statistical processes and choose which to
use for particular data analysis applications
4.Learn to interpret statistical results as a basis for
decision-making
6.Collaborate effectively to use statistical analysis to
7.Communicate results of statistical analysis
logically and persuasively
6.Collaborate effectively to use statistical analysis to
7.Communicate results of statistical analysis
logically and persuasively
Understand factors that contribute
to effective teamwork.
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5
5.1
5.2
6
6.1
ethical reasoning skills,
understand social, civic, and
professional responsibilities and
aspire to add value to society.
Specifically, students will:
Understand professional codes of
conduct.
Low
1. Understand the concepts of descriptive statistics,
inference, summarizing, and sampling
2.Recognize different models of statistical processes
3.Explain statistical processes and choose which to
use for particular data analysis applications
4.Learn to interpret statistical results as a basis for
decision-making;
6.Collaborate effectively to use statistical analysis to
7.Communicate results of statistical analysis
logically and persuasively
1. Understand the concepts of descriptive statistics,
inference, summarizing, and sampling
3.Explain statistical processes and choose which to
use for particular data analysis applications
4.Learn to interpret statistical results as a basis for
decision-making
6.Collaborate effectively to use statistical analysis to
7.Communicate results of statistical analysis
logically and persuasively
Recognize ethical challenges in
appropriate courses of action.
communicators to facilitate
information flow in organizational,
social, and intercultural contexts.
Specifically, students will:
Identify and assess diverse personal
and organizational communication
goals and audience information
needs
6.2
Understand individual and group
communications patterns and
dynamics in organizations and other
professional contexts
6.3
Demonstrate an ability to gather
and disseminate information and
communicate it clearly, logically,
and persuasively in professional
contexts.
Goal 5
Low
BUAD310 Course Objectives 4,6,7 support Goal
6
4.Learn to interpret statistical results as a basis for
decision-making;
6.Collaborate effectively to use statistical analysis to
7.Communicate results of statistical analysis
logically and persuasively
4.Learn to interpret statistical results as a basis for
decision-making;
6.Collaborate effectively to use statistical analysis to
7.Communicate results of statistical analysis
logically and persuasively
6.Collaborate effectively to use statistical analysis to
7.Communicate results of statistical analysis
logically and persuasively
- 10 -
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