UNIVERSIDAD DE ESPECIALIDADES ESPÍRITU SANTO
FACULTAD DE ESTUDIOS INTERNACIONALES
INTERNATIONAL CAREERS PROGRAM
SYLLABUS
COURSE: Statistics II
SCHEDULE: Mon-Thurs 7h30–9h50
FACULTY: Cesar Alvarez, Msc.
BIMESTER: Fall I 2006
ACADEMIC UNITS/CRÉDITS: 3 UEES
(S.N.C.C. 4.8 )
PRE REQUISITES: Calculus I, Calculus II, Statistics I
ROOM:
CONTACT HOURS: 40
NON CONTACT HOURS: 96
1. COURSE DESCRIPTION
Statistics II is the second of two introductory courses in Statistics. The application of
statistical tools learned along this course is very important in the development of both
short-term strategies and strategic planning in today’s business environment. This
course will demand basic Excel knowledge from the students.
This course will cover the following topics:
 Decision making tools
 Hypothesis testing for proportions
 Analysis of variance
 Correlation analysis
 Simple and multiple regression analysis
 Chi Square tests
 Game theory
2. OBJECTIVES
a. GENERAL
Students will develop the capacity to understand and construct economic models based
on the understanding of the behaviour of a set of variables affecting a variable of
interest.
b. SPECIFIC
Gain abilities in the management of hypothesis testing, simple regression, multiple
regression and correlation analysis as a tool for optimizing the decision making process
and forecasting real business economics trends.
Agosto 2006
3. COURSE CONTENT OUTLINE
DATE &
Specific
SESSIONS
Competencies
Sept 5
Has a better
understanding of
how statistical tools
will be used to
achieve course
goals.
Sept 6
Compares location
and dispersion
parameters from
one or two
populations, in
order to take
decisions.
Sept 7
Sept 8
CONTENT
Introduction to the
course
Regression analysis
project requirements
NON CONTACT
HOURS
Read general
concepts about
probability, mean,
standard deviation (
2 hours)
Investment analysis
exercise: Which
investment
alternative is the
best one ( 2 hours)
In class
exercises
Tests concerning to
differences between
means and standard
deviations
Sequential decision
The hamburger
store case:
Calculation of
mean, standard
deviation, and
development of
decision tree (3
hours)
The hamburger
store case:
Calculation of
maximax, maximin
and minimax regret
(2 hours)
Preparation of
Project Proposal +
obtention of data to
be used in the
project (5 hours)
In class
exercises
Aept 12
Makes decisions
based on
probabilistic
decision trees.
Probabilistic decision
trees
Sept 13
Constructs control
charts to control
quality of any type
of production
process.
Quality control and
improvement
Quality and role of
statistics
Product and
process design
Assessing
conformance
Quality control and
Quality control
improvement
exercise (3 hours)
Quality and role of
statistics
Product and
Agosto 2006
In class
exercises
Decision making
tools:
Mean and standard
deviation as tools for
decision making
Decision making
tools
Maximax
Maximin
Minimax Regret
Sept 14
ASSESMENT
In class
exercises
Project Proposal
Review
In Class
exercise
Sept 15
Tests statistical
hypothesis
regarding
parameters from
one or more
populations.
Sept 19
Sept 20
Sept 21
Sept 22
Sept 27
Explains the
behaviour of one
quantitative
variable in terms of
other quantitative
or qualitative
variables.
Sept 28
process design
Assessing
conformance
Hypothesis testing
Null hypothesis
Alternative
hypothesis
Determination of
acceptance or
rejection of the null
hypothesis
Hypothesis testing
Determination of
acceptance or
rejection of the null
hypothesis
One tail analysis and
rwo tail analysis
(hypothesis testing)
Hypothesis testing
Determination of
acceptance or
rejection of the null
hypothesis
One tail analysis and
two tail analysis
(hypothesis testing)
Regression analysis
Introduction
General concepts
Simple Regression
Multiple Regression
Multiple regression
analysis
R square
F value
Residuals
Multiple regression
analysis
R square
F value
Residuals
Dummy variables
Sept 29
Predicts future
observations from a
single variable by
using past
Agosto 2006
Forecasting
methods
Naive models
Moving averages
Preparation of
Project Proposal +
obtention of data to
be used in the
pñroject (5 hours)
Project Proposal
Review
Hypothesis testing
homework (4
hours)
In class
exercises
Exerscises for the
mid term exam (15
hours)
Project: Regression
analysis (10 hours)
Project review
Project review
Project: Regression
analysis (5 hours)
Projet review
Project: Forecasting Projet review
analysis (5 hours)
Sept 30
observations over
equal well defined
time periods.
MID TERM
EXAM
Oct 4
Forecasting
methods
Project: Forecasting Projet review
analysis (5 hours)
Moving averages
Exponential
smoothing
Oct 5
Forecasting
methods
Project: Forecasting Projet review
analysis (5 hours)
Exponential
smoothing
Time series
analysis: CPI
Oct 6
Project review
Project: Forecasting Projet review
analysis (5 hours)
Oct 7
Project review
Oct 11
Oct 12
Computes gain and
loss expectations of
stochastic processes
called “games”.
Game theory
Introduction
General concepts
Homework Game
Theory
Game theory
Mix strategy vs Pure (5 hours)
strategy
Calculation of
frequencies of the
game
Value of the game
In class
exercises
Oct 13
Game theory
Mix strategy vs Pure
strategy
Calculation of
frequencies of the
game
Value of the
game
Oct 14
Game theory
Agosto 2006
Exercises for the
final exam (15
hours)
Final exam
Mix strategy vs Pure
strategy
Calculation of
frequencies of the
game
Value of the
game
Oct 18
Compares one or
more variables
measured over
elements belonging
to more than two
populations or
groups.
Analysis of
variance
Anova Analysis
Oct 19
REVIEW FOR
FINAL
Oct 19
FINAL EXAM
Oct 20
Project due
4. METHODOLOGY
Active class participation from the students is encouraged during the course.
Students are responsible for studying after and before class, so the program can
be achieved in an effective and efficient way. In addition, students are going to
be evaluated with in-class questions, exercises and tests based on the readings
assigned for each class session.
According to UEES rules, only 20% absences are permitted; which means six
class sessions.
When class starts, the instructor will wait a maximum of fifteen minutes before
closing the door. Students who arrive late will not be allowed to come into the
class.
Please turn off cellular phones during class.
According to UEES policy, students are required to read a minimum of 400
pages per course. In order to comply with this policy, students are responsible
for reading and preparing the class lecture with anticipation of each class session
Agosto 2006
Homework and projects should be turned in at the beginning of each class
session. Late homework will be accepted with a penalty of 50% of the grade
given for that assignment. After the instructor has handled back as assignment,
no more assignments will be accepted In addition, being absent the day of an
assignment is due is not an excuse for not handling in the assignment on time.
Research, homework, and project assignments will be based on the original work
of each student
If a student without an authorization is not present on the day the mid-term or
final exams are given; the student will need to get permission from the ICP Dean
to have the right for taking the exam. However, the exam will be evaluated over a
maximum grade of 80.
5. ASSESSMENT
Mid Term exam:
Final Exam
Project
Homework
Participation
25%
25%
20%
20%
10%
6. BIBLIOGRAPHY
6.1 REQUIRED
Neter, J. Wasserman, W. Whitmore, G.
(1993). Allyn and Bacon.
Applied Statistics 4th Edition
6.2 COMPLEMENTARY
David Anderson, Dennis Sweeney, Thomas Williams, Statistics for
Business and Economics (2004)
6.3 HANDOUTS:
To be defined throughout the course.
6.4 WEBLIOGRAPHY:
To be defined throughout the course.
7. FACULTY INFORMATION
Agosto 2006
NAME:
Cesar A. Alvarez, Msc
ACADEMIC CREDENTIALS--UNDERGRAD:
Ingenieria en Estadistica Informatica, ESPOL
GRADUATE:
Master of Science, University of New Orleans
E – mail:
[email protected]
Agosto 2006