Data Analysis BUS 304
College of Business Administration
California State University San Marcos
Course Information:
1 Title: Data Analysis
2 Course number: BUS 304
3 Semester: Spring 2007
4 Prerequisites: All lower-division pre-business core + University computer
competency requirement
5 Sections: 1 & 9
6 Instructor: Dr. Edward S. Balian
7 Office: To be announced.
8 Telephone : To be annonced.
9 E-mail: To be announced.
10 Homepage: http://public.csusm.edu/esblastname
To be announced.
11 Course page: http://courses.csusm.edu/bus3digitcoursenumberesb To
be annonced.
12 Password protected course page:
http://courses.csusm.edu/bus3digitcoursenumberesb/download
To be
announced.
13 Class hours: Section 1: m 800am -- 850am, m, w 0900am-- 1025am
14
15 Office hours:
Section 9: tues 1500 -- 1550,
thur 1600 -- 1725
Tuesday 2-3PM and Thursday 3-4pm or by appointment.
Textbook:
Required Text:
D. F. Groebner, P. W. Shannon, P. C. Fry, and K. D. Smith, "Course in Business
Statistics". Prentice Hall, 6/E 2006.
Other References:
1 D. F. Groebner, P. W. Shannon, P. C. Fry, and K. D. Smith, "Business
Statistics: A Decision Making Approach". Prentice Hall, sixth edition 2005.
2 M. K. Pelosi and T. M. Sandifer, " Doing Statistics for Business with Excel",
John Wiley & Sons, Inc. second edition 2002.
3 A. H. Kvanli, R. J. Pavur and K. B. Keeling, "Introduction to Business
Statistics", South-Western, Edition 6, 2003.
Course description and objectives:
In order to stand out in today's competitive job market, new business school
graduates need to bring to an organization special skills and abilities that give
them the potential to hit the ground running and contribute immediately. One
area where a student can have an immediate competitive advantage over both
new graduates and existing employees is in the application of statistical analysis
skills to business problems. Our intent in this course is to build your statistical
back ground and to give you the statistical skills necessary to meet the needs of
business and the real-world decision-making problems. In this course, we
discuss real-world applications as a motivation for learning business statistics.
We will focus on decision making and business applications and provide you with
an understanding of the roll of business statistics in decision making.
To enhance the students' appreciation for business statistics, we emphasize
computer-based analysis, rather than manual computation. To this end, Microsoft
Excel is used extensively throughout the course. Minitab may also be used as a
supplement to Excel.
Learning Outcomes:
Following this course the students should
1 Know the data collection methods and understand how to categorize data.
2 Construct and interpret a scatter plot, joint frequency table, pareto chart,
frequency histogram and various types of bar charts.
3 Compute and understand the mean, median, mode and variance for a set
of data.
4 Compute the coefficient of variation and z scores and understand how
they are applied in decision-making situations.
5 Be able to apply the common rules of probability and to identify the types
of processes that are presented by discrete probability distributions.
6 Understand the main approaches to assessing probabilities and determine
probabilities associated with binomial and poisson distributions.
7 Be able to discuss the important properties of the normal probability
distribution and calculate probabilities using the normal distribution table
and be able to apply the normal distribution in appropriate business
situations.
8 Understand the concept of sampling error and the importance of the
Central Limit Theorem.
9 Be able to determine the mean and standard deviation of the sampling
distribution of the population mean and proportion.
10 Construct and interpret a confidence interval estimate for a single
population mean using both the standard normal and t distribution.
11 Determine the required sample size for estimating a single population
mean.
12 Establish and interpret a confidence interval estimate for a single
population proportion.
13 Formulate null and alternative hypotheses for applications involving a
single population mean, proportion, or variance.
14 Know how to use the test statistic, critical value, and p -value approach to
test the null hypothesis.
15 Calculate and interpret the simple correlation between two variables.
16 Understand the basic assumptions behind single and multiple regression
models.
17 Recognize some potential problems if regression analysis is used
incorrectly.
Course Requirements:
Your course grade will be based on 4 exams, 4 homework assignments, a team
project and class participation.
Homework assignments: (15%)
Team Project and group presentation: (15%)
Exam 1: Chapters 1-3, Open book (10%)
Exam 2: Chapters 4-5, Open book (10%)
Exam 3: Chapters 6-8, Open book (10%)
Final Exam: Chapters 1-8, 12, and 13 (cumulative), Closed book & Open book
(30%)
Class participation: (10%)
Homework assignments:
Homework assignments are designed to help you learn the mechanics of the
methods discussed in class and to give you an opportunity to apply these
concepts in a straightforward manner. In addition to their value as learning
exercises, doing a careful and thorough job on the homework assignments is the
best preparation for the examinations of the course.
Homework policy:
1 There will be 4 assignments throughout the semester which
will be posted.
2 You must submit a hard copy at the beginning of the class
when it is due.
3 The first page of your report should be a cover page: your
name, homework number, course number, date, etc.
4 Each problem must be answered in a separate page and in
the same order as given.
5 All pages must be stapled together.
6 No late assignment will be accepted.
Team Project and group presentation:
The objective of this is to permit students to tailor the course to their own
interests, whether they are in HTM, GBM, M&M, or Accounting/Finance. The
project is designed to acquaint students with one specific area of application of
statistics. Each team must submit a one-page proposal on December 1.
Writing Requirement (as stated in the catalog): All CSU students
must demonstrate competency in writing skills as a requirement for
graduation. This requirement mandates that every course at the
university must have a writing component of at least 2500 words
(approximately 10 pages). To achieve this requirement in this
course, each team is required to present their findings in the last
week of class and hand in a final report. The general plan of the
final report is as follows:
1 Executive Summary (1-2 pages): A clear summary of the
project: issues raised by the managerial situation, your
approach in resolving the situation and the final
recommendations.
2 Main body (8-10 pages): A detailed analysis and explanation
of the analytical approach followed by the students in solving
the problem.
3 Conclusion (1-2 pages): A clear, concise summary of the
recommendations for the specific actions to be taken
targeted at the manager who may decide to implement these
recommendations.
Sample projects from previous years are available in my office.
Grading Standards:
94-100 90 < 94 85 < 90 80 < 85 75 < 80 70 < 75 65 < 70 60 < 65 0 < 60
A
A-
B+
B
B-
C+
C
C-
F
Tentative Course Schedule:
Date
Topics
Notes
Weeks 1,2, and 3
Chapters 1-3 Descriptive
Statistics
 Histogram, charts and
graphs
Measure of central
tendency and variation
Coefficient of
variation
Standardized data
values
Assignment 1 due
Chapters 1-3
 Review
Solution to
Assignment 1
Weeks 4, 5, 6, and 7
Chapters 4 and 5 probability
 Probability rules
Binomial
distribution
Exam 1
Normal
distribution
Assignment 2 due
Chapters 4-5
 Review
Exam 2
Solution to
Assignment 2
Weeks 8, 9, 10, & 11
Chapters 6-8 Sampling distributions
 Sampling distribution
Confidence
Intervals
Sample size
Hypothesis testing
Chapters 6-8
 Review
Solution to
Assignment 3 due
Exam 3
Assignment 3
Weeks 12, 13, and 14
Chapters 12 and
13 Regression Analysis
 Simple linear regression
Multiple linear
regression
Assignment 4 due
Final review
Week 15
Group presentation
Final Exam
Week 16
Section 1: May 14 7-9am
Section 9: May 15 1:45pm3:45pm
Project proposal due
Academic Honesty Statement: Students will be expected to adhere to standards
of academic honesty and integrity, as outlined in the Student Academic Honesty
Policy. All written work and oral presentation assignments must be original work.
All ideas/material that are borrowed from other sources must have appropriate
references to the original sources. Any quoted material should give credit to the
source and be punctuated with quotation marks.
ADA statement: Students with disabilities who require reasonable
accommodations must be approved for services by providing appropriate and
recent documentations to the Office of Disabled Student Services (DSS). This
office is located in Craven Hall 5205, and can be contacted by phone at (760)
750-4905, or TTY (760) 750-4909. Students authorized by DSS to receive
reasonable accommodations should meet with me during my office hours in
order to ensure confidentiality.
NOTE: It is the student’s responsibility to understand and follow the University Policies as stated in the
catalog.