Download Syllabus for MATH 211 - Introduction to Probability and Statistics I

Syllabus for MATH 211 - Introduction to Probability and Statistics I
Objectives
This course provides an introduction to some concepts of probability and statistics with applications for students who would
like to have careers in information intensive fields. Topics include: describing data and summarizing descriptive relationships;
probability and its postulates; probability distributions for discrete random variables; probability distributions for continuous
random variables and sampling distributions. The course provides many examples of most common statistical methods and
assumptions lead to useful comprehension of business and economic problems.
Textbook:
“Statistics for Business and Economics” by P. Newbold, W.L. Carlson, B. Thorne, 7/e, Prentice Hall.
Reference Book:
“Essentials of Contemporary Business Statistics” by T.A. Williams, D.J. Sweeney, D.R. Anderson, 2007, Thomson.
Web Page: http://dm.ieu.edu.tr/statistics.php
Grading
Exam
1st Midterm Exam
2nd Midterm Exam
Final Exam
Class Participation (Quiz & Homework )
Ratio
25%
25%
40%
10%
Important: If you miss an exam and have an official excuse, report it
immediately after the exam, otherwise you will get 0 (zero). Common
make-up exam will cover all topics and will be at the end of semester.
Course Outline
1. Decision making in an uncertain environment. Describing data and summarizing descriptive relationships.
2. Classification of variables. Graphs to describe categorical variables. Graphs to describe time-series data. Graphs to
describe numerical variables. Tables and graphs to describe relationships between variables. Data presentation errors.
3. Measures of central tendency.
4. Measures of variability. Chebychev's Theorem. Coefficient of Variation. Relationships between variables.
5. Random experiment, outcomes, events. Permutations and combinations. Probability and its postulates.
6. Classical probability. Relative frequency. Subjective probability. Probability rules. Conditional probability. Statistical
independence.
7. Bivariate probabilities. Bayes’ theorem.
8. Random variables. Probability distributions for discrete random variables. Properties of discrete random variables.
Binomial distribution.
9. Expected value of a discrete random variable. Variance of a discrete random variable. Mean and variance of linear
functions of a random variable.
10. Hypergeometric distribution. The Poisson probability distribution. Jointly distributed random variables.
11. Continuous random variables. The Uniform distribution. Expectations for continuous random variables. Expectations
for linear functions of continuous random variables.
12. The Normal distribution. Normal probability plots. Normal approximation. Exponential distribution.
13. Sampling from a population. Sampling distributions of sample means.
14. Central limit theorem. Sampling distributions of sample proportions. Sampling distributions of sample variance.
Rules
Attendance is an essential requirement of this course and is the responsibility of the student. Class begins promptly and you are
expected to be present at the beginning and at the end of each class session.
Notes
Homework problems are the best preparation for exams. You should try to work the homework problems without constant
reference to the text or passively receiving help from others. We encourage discussing problems with others, but you should try
to do the actual problems yourself. If you have gotten the idea about how to solve a problem from another person or by looking
things up in the text, try to do a related problem without outside aid.
• The content of this syllabus can be changed by the instructor at any time by informing the related department’s head.
• The student is supposed to be aware of the facts and notices written in this syllabus.