Fall 2009

MATH 3332/01 - Probability and Statistical Inference

Instructor

Dr. Anda Gadidov

Office

Science Building Room 529

Contact

(770)423-6098, e-mail: agadidov@kennesaw.edu
All emails should originate from the students’ netid.student.kennesaw.edu account or from their WebCT account. Our e-mail system allows for email filtering software that blocks certain domains, one of which could be your commercial email provider.  For more information on setup and use of your email account, go to https://students.kennesaw.edu/email.

Office hours

MW 9:30am- 10:45am and 1:00pm-2:00; other times by appointment

Class meets

MW 11:00pm-12:15pm in CL1007

Text

Probability and Statistics for Engineering and the Sciences, seventh ed., by Jay L. Devore,  Thomson Learning, ISBN13: 978-0-495-38217-1

Prerequisites

Math 1190 Calculus I grade of C or better

Description

This course is designed to introduce the student to probability and both descriptive and inferential statistics. Topics include: random variables and probability distributions, expectation and variance of random variables, properties of estimators, exploratory data techniques, confidence intervals, hypothesis tests for population mean and proportion. Minitab, Maple and TI 83 Plus calculator will be used at times to complement the learning process. You can download Citrix that will give you remote access to Minitab from

http://science-citrix.kennesaw.edu/Citrix/MetaFrame/auth/login.aspx and follow the directions for installation.

Learning 
outcomes

1. Students should acquire appropriate vocabulary (population, sample, census, parameter, statistic) and notation.
2. Students will be able to correctly plot and describe statistical data.
3. Students will be able to correctly interpret statistical plots.
4. Students will understand the importance of measures of center and variation.
5. Students will understand basic probability concepts and be able to use them accordingly.
6. Students will learn and understand the concept of random variable and its probability distribution.

7. Students will know how to compute probabilities using the Hypergeometric, Binomial and Poisson models.
8. Students will know to distinguish between discrete and continuous distributions and be able to apply the concepts to real- life problems.

9. Students will know how to use Calculus techniques to find the expected value and variance of a random variable and be able to apply the concepts to real world problems.

10. Students will know how to apply the Central Limit Theorem to applications involving sample means and sample proportions.
11. Students will be able to build confidence intervals to estimate population parameters such as means and proportions from statistical data.
12. Students will be able to successfully use software to describe, analyze, and perform inferential statistics.
13. Students will gain appreciation for the importance of statistics in everyday life.

Topic outline

Chapter 1: Overview and Descriptive Statistics: basic concepts, mean, variance and standard deviation; exploratory data analysis. 

Chapter 2: Probability: properties of probability; counting methods; conditional probability; independence. 
Chapter 3: Discrete Distributions: discrete random variables; expected value; the Bernoulli distribution, hypergeometric and the Poisson distribution. 
Chapter 4: Continuous Distributions: continuous random variables and probability density functions; the Uniform, the Normal distribution, the Gamma family of distributions. 
Chapter 5: Joint Probability Distributions and Random Samples; distribution of sums of random variables; random functions associated with normal distributions; the Central Limit Theorem. 
Chapter 6: Point estimation: general concepts. 
Chapter 7: Confidence intervals: confidence intervals for means, proportions and variances; sample size. 
Chapter 8: Tests of Statistical Hypotheses; tests for means, proportions and variances; tests of the equality of two normal distributions.

Grading

Homework will be assigned and be part of the grade. I encourage you to work the problems since this is the best way to prepare for this course.  Check my homepage http://math.kennesaw.edu for updates on the course. You are also encouraged to attend the weekly talks, and monthly Math Nights organized by the Mathematics Department. At these talks you will see researchers presenting their work, students presenting a Capstone experience in general a wide array of applications of Mathematics. For each session you attend there will be a 1 point bonus added to your exam of choice.

Your grade will be based on your performance on homework assignments, class participation, quizzes and tests. There will be a quiz almost every week, three semester exams and a final comprehensive exam. Quizzes will be graded on a scale of 0 to 10 and only the best ten grades will count toward your final grade. The final is scheduled on Wednesday, December 9, 11:00 am- 1:00pm. 
Make-up quizzes or tests will not be given unless there are exceptional circumstances.  If you must miss a test, you should notify me in writing before the scheduled test time. 
Grades will be assigned as follows: 

Quizzes	100p	A	90% and above
HW	100p	B	between 80% and 90%
Exam 1	100p	C	between 70% and 80%
Exam 2	100p	D	between 60% and 70%
Exam 3	100p	F	below 60%
Final exam	125p
Total	625p

Tentative schedule of exams:  Exam 1: Sept. 10 , Chapters 1-3
                                             Exam 2: Oct. 8, Chapters 3-4
                                             Exam 3: Nov. 12, Chapters 5-7

Academic
misconduct

Every KSU student is responsible for upholding the provisions of the Student Code of Conduct, as published in the Undergraduate and Graduate Catalogs. Section II of the Student Code of Conduct addresses the University’s policy on academic honesty, including provisions regarding plagiarism and cheating, unauthorized access to University materials, misrepresentation/falsification of University records or academic work, malicious removal, retention, or destruction of library materials, malicious/intentional misuse of computer facilities and/or services, and misuse of student identification cards. Incidents of alleged academic misconduct will be handled through the established procedures of the University Judiciary Program, which includes either an “informal” resolution by a faculty member, resulting in a grade adjustment, or a formal hearing procedure, which may subject a student to the Code of Conduct’s minimum one semester suspension requirement.

Withdrawal
policy

Students who find that they cannot continue in college for the entire semester after being enrolled, because of illness or any other reason, need to complete an online form. To completely or partially withdraw from classes at KSU, a student must withdraw online at www.kennesaw.edu, under Owl Express, Student Services.

The date the withdrawal is submitted online will be considered the official KSU withdrawal date which will be used in the calculation of any tuition refund or refund to Federal student aid and/or HOPE scholarship programs. It is advisable to print the final page of the withdrawal for your records. Withdrawals submitted online prior to midnight on the last day to withdraw without academic penalty will receive a “W” grade. Withdrawals after midnight will receive a “WF”. Failure to complete the online withdrawal process will produce no withdrawal from classes. Call the Registrar’s Office at 770-423-6200 during business hours if assistance is needed.

Students may, by means of the same online withdrawal and with the approval of the university Dean, withdraw from individual courses while retaining other courses on their schedules. This option may be exercised up until October 12, 2009.

This is the date to withdraw without academic penalty for Spring Term, 2009 classes. Failure to withdraw by the date above will mean that the student has elected to receive the final grade(s) earned in the course(s). The only exception to those withdrawal regulations will be for those instances that involve unusual and fully documented circumstances.

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