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CAIS 102 — Business Statistics I
School of Business — Fall 2013
Instructor: Timothy Dorr, DM
Office:
Man 217B
Hours:
As shown & by appt
Email:
[email protected]
Time
9:30-10:45
11:00-1:00
Monday
Prerequisites: CAIS 101
Class Meetings: As shown
Room: Computer Lab
Home Phone: 858-1619 (be reasonable)
Tuesday
Office
1:30-2:45
CAIS 102
Wednesday Thursday
Office
Office
Office
Office
CAIS 102
3:00-4:15
Office
Office
Office
4:30-5:45
Office
CAIS 101
CAIS 101
Alt. Fridays
Office
Open Computer
Lab
Open Computer
Lab
Final Exam Schedule: Week of Dec 9 – Dec 13, 2013
Course
Date
Time
CAIS 101
CAIS 102
Note: Final Exam schedule is unavailable at the time of publication.
Course Content and Description:
Today businesses are awash in data, and what businesses will pay for is an ability to make sense
out of terabytes (a thousand gigabytes) of data. Business Statistics is a way to summarize data and to
infer characteristics of such large populations of data. It is not mathematics. It is one of the most
widely applicable tools available to business people, and also one that is not widely mastered.
Knowledge of statistics and data management will make you an exception and thus more employable.
This is the second of two undergraduate courses in the use of statistics in business. Again, this is
not a math course. This is a course about how to use data for making more rigorous business decisions.
We begin with a review of descriptive statistics, discrete probability distributions, and the normal
distribution which were covered in CAIS 101. For the remainder of the semester we will examine the
application of statistics through sampling, confidence interval estimation, hypothesis testing, and nonparametric statistics. As in CAIS 101we will continue to use Excel for the work in this course.
Additionally we will examine other proprietary statistics applications.
Topics:
1. Review of descriptive statistics, discrete distributions, and the normal distribution.
2. Introduction to Probability
a) Definition and applications
b) Random Variables: discrete and continuous distribution
3. Sampling and the Central Limit Theorem
a) Sampling techniques
b) Application of the Central Limit Theorem
ASSESSMENT 1
4. Statistical estimation and Confidence Intervals
a) Measuring the relationship between statistics (samples) and parameters (populations).
b) Validating the strength of an estimate
ASSESSMENT 2
5. Hypothesis Design and Testing
a) Defining a hypothesis: what to test
b) Null versus alternative Hypotheses
c) Hypothesis tests of the mean using interval data
d) Hypothesis tests of the mean using ordinal data
ASSESSMENT 3
6. Two-sample Hypothesis Testing
a) Evaluating statistically significant differences among samples
b) Statistics selection based on sample size variations
c) Statistics application
d) Sample mean variation validity: p-values
e) Testing proportion data
ASSESSMENT 4
7. Introduction to Inferential Statistics
a) Analysis of Variance (ANOVA)
b) Correlation and Linear Regression
8. FINAL EXAM
Expected Outcomes:
At the end of this course a successful student will be equipped to discuss the application of
appropriate statistical tests which use sample measurements for mean and variance as ‘best’
estimators for a population that exhibits normal data distribution characteristics.
Within a business setting this student will be ready to discuss various tactical marketing
research projects and proposals and to make informed decisions regarding their respective value to an
organization. The student will be prepared to take additional graduate level courses in business
quantitative analysis.
Text and Recommended Reading:
The official text for the course:
Statistical Techniques in Business & Economics, 12th ed., Lind, Marchal, and Wathen, New York, NY:
McGraw-Hill, Irwin.
I will loosely follow the chapters in the text and you must buy a textbook. To stay with the material
being covered you are encouraged to have the text within three weeks of the start of class. If this
becomes an issue let me know. The text serves as an ancillary learning tool and resource. In a real
business situation if you have a problem you look up the appropriate principles in a reputable resource
and apply those principles to your specific problem. That said, we will be doing some problems from
the text. Such problems are contrived to illustrate a specific principle or application.
I encourage students of modest financial means to find a used copy of the text online rather than
pay full price at the bookstore. Introductory Statistics have not changed much in the last fifty years
and previous editions of the text from a few years ago are entirely acceptable. If you choose to use an
edition from more than five years ago, you may find that the software references are somewhat dated,
even though the subject material is current.
Grading Application and Ranges:
Grades are based on performance not on effort, desire, or need. English skills, written and spoken,
are a part of every student's grade on every assignment. If you need a particular grade, to maintain
your scholarship status, your athletic eligibility, or any other reason, the time to start working toward
fulfilling that need is now.
In-term assessments:
40%
Class participation:
20%
Final Exam:
40%
Failure to earn a score of 50% or greater on the final will result in a course failure.
Grade
Percentage
A
AB+
B
BC+
C
CD+
D
DF
95+ 90-94 87-89 84-86 80-83 77-79 74-76 70-73 67-69 64-66 60-63 <60
At the end of the course you will have a raw course score available through the Canvas® gradebook.
This grade may be adjusted to reflect the application of a normal distribution in keeping with statistical
analysis prior to your grade being submitted to the registrar.