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MA 305 Probability
Pogge, James Todd


Mission Statement: The mission of Park University, an entrepreneurial institution of learning, is to provide access to academic excellence, which will prepare learners to think critically, communicate effectively and engage in lifelong learning while serving a global community.

Vision Statement: Park University will be a renowned international leader in providing innovative educational opportunities for learners within the global society.

Course

MA 305 Probability

Semester

FA 2008 HO

Faculty

Pogge, James Todd

Title

Assistant Professor of Mathematics

Degrees/Certificates

Ph.D., Mathematics (Number Theory)
M.S., Mathematical Sciences (Pure Mathematics)
B.S., Mathematics/Computer Science (double major)

Office Location

SC 105C (Must enter through SC 105)

Office Hours

Monday, 9:15-10:35; Tuesday, 10:10-11:10; Wednesday, 9:15-10:35; Thursday, 10:10-11:10; Friday, 9:15-10:35

Daytime Phone

816-584-6575

E-Mail

todd.pogge@park.edu

Semester Dates

18 August 2008 - 12 December 2008

Class Days

--T-R--

Class Time

11:35 - 12:50 PM

Prerequisites

MA 131 or equivalent

Credit Hours

3


Textbook:
Miller, Irwin; Miller, Marylees. John E. Freund's Mathematical Statistics with Applications. Seventh Edition. Pearson Prentice Hall. 2004. (ISBN: 0-13-142706-7) (ISBN 13: 9 780131 427068)

Textbooks can be purchased through the Parkville Bookstore

Additional Resources:

McAfee Memorial Library - Online information, links, electronic databases and the Online catalog. Contact the library for further assistance via email or at 800-270-4347.
Career Counseling - The Career Development Center (CDC) provides services for all stages of career development.  The mission of the CDC is to provide the career planning tools to ensure a lifetime of career success.
Park Helpdesk - If you have forgotten your OPEN ID or Password, or need assistance with your PirateMail account, please email helpdesk@park.edu or call 800-927-3024
Resources for Current Students - A great place to look for all kinds of information http://www.park.edu/Current/.


Course Description:
MA305 Probability: Essentially a non-calculus approach to the theory and statistical applications of probability. Topics include discrete and continuous random variables, density and distribution functions, probability models, non-parametric statistics. 3:0:3 Prerequisite: MA131 or equivalent.

Educational Philosophy:

I believe that most things are easy once shown, but tend to be difficult until shown. So a student shall be encouraged to address mathematical concepts sevearl times primarily through doing problems. One needs a vocabulary. So there will be quizzes on vocabulary as we work on a mathematical language for probability.
 
Class time is primarily presentation with slight time for refinement, but time is made for general questions. However, teaching often takes place during an office hour where individual questions and problems can be addressed more adequately.

Learning Outcomes:
  Core Learning Outcomes

  1. Identify and apply properties and operations of set theory
  2. Apply set theory to sample spaces and events
  3. Prove and apply basic theorems of probability
  4. Compute probabilities using combinations or permutations
  5. Apply the binomial theorem and binomial coefficients
  6. Solve problems using discrete random variables and their associated probability functions


Core Assessment:

-Periodic assignments


-Quizzes


-Tests

Link to Class Rubric

Class Assessment:
Grades are determined from quizzes, tests, and the final examination. Grades of A(90%), B(80%), C(70%), D(60%), and F(less than 60%) will be given. A final is mandatory. The final examination is worth 150 points. The other three tests are worth 100 points each. The instructor reserves the right to change the syllabus.

Grading:
See Above

Late Submission of Course Materials:
Assignments not submitted on the due date will receive a grade of "zero".

Classroom Rules of Conduct:
All students are expected to be present and on time with homework assigned completed.

Course Topic/Dates/Assignments:
Chapters 1, 2, 3, 4, 5, 6, and 7

Academic Honesty:
Academic integrity is the foundation of the academic community. Because each student has the primary responsibility for being academically honest, students are advised to read and understand all sections of this policy relating to standards of conduct and academic life.   Park University 2008-2009 Undergraduate Catalog Page 87

Plagiarism:
Plagiarism involves the use of quotations without quotation marks, the use of quotations without indication of the source, the use of another's idea without acknowledging the source, the submission of a paper, laboratory report, project, or class assignment (any portion of such) prepared by another person, or incorrect paraphrasing. Park University 2008-2009 Undergraduate Catalog Page 87

Attendance Policy:
Instructors are required to maintain attendance records and to report absences via the online attendance reporting system.

  1. The instructor may excuse absences for valid reasons, but missed work must be made up within the semester/term of enrollment.
  2. Work missed through unexcused absences must also be made up within the semester/term of enrollment, but unexcused absences may carry further penalties.
  3. In the event of two consecutive weeks of unexcused absences in a semester/term of enrollment, the student will be administratively withdrawn, resulting in a grade of "F".
  4. A "Contract for Incomplete" will not be issued to a student who has unexcused or excessive absences recorded for a course.
  5. Students receiving Military Tuition Assistance or Veterans Administration educational benefits must not exceed three unexcused absences in the semester/term of enrollment. Excessive absences will be reported to the appropriate agency and may result in a monetary penalty to the student.
  6. Report of a "F" grade (attendance or academic) resulting from excessive absence for those students who are receiving financial assistance from agencies not mentioned in item 5 above will be reported to the appropriate agency.

Park University 2008-2009 Undergraduate Catalog Page 89-90

Disability Guidelines:
Park University is committed to meeting the needs of all students that meet the criteria for special assistance. These guidelines are designed to supply directions to students concerning the information necessary to accomplish this goal. It is Park University's policy to comply fully with federal and state law, including Section 504 of the Rehabilitation Act of 1973 and the Americans with Disabilities Act of 1990, regarding students with disabilities. In the case of any inconsistency between these guidelines and federal and/or state law, the provisions of the law will apply. Additional information concerning Park University's policies and procedures related to disability can be found on the Park University web page: http://www.park.edu/disability .



Rubric

CompetencyExceeds Expectation (3)Meets Expectation (2)Does Not Meet Expectation (1)No Evidence (0)
Evaluation                                                                                                                                                                                                                                                 
Outcomes
                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    
Can use calculus to derive properties of continuous probability distributions.
 
Can apply properities of continuous probability distributions
 
Cannot apply properties of continuous probability distributions.
 
Makes no attempt to apply the properties of continuous probability distributions.
 
Synthesis                                                                                                                                                                                                                                                  
Outcomes
                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    
Can use moment-generating functions to derive properties of probability density functions with 100% accuracy.
 
Can use moment-generating functions to derive properties of probability density functions with at least 80%  accuracy.
 
Can use moment-generating functions to derive properties of probability density functions with less than 80%  accuracy.
 
Makes no attempt to use a moment generating function.
 
Analysis                                                                                                                                                                                                                                                   
Outcomes
                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    
Can compute the mean and standard deviation of the binomial probability distribution using sigma-notation with 100% accuracy.
 
Can compute the mean and standard deviation of the binomial distribution using sigma-notation with at least 80% accuracy.
 
Can compute the mean and standard deviation of the binomial distribution using sigma-notation with less than 80% accuracy.
 
Makes no attempt to compute the mean and standard deviation of the binomial probability distribution.
 
Terminology                                                                                                                                                                                                                                                
Outcomes
                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    
Can define such terms as sample space, event, singleton, union, intersection, conditional probability, universal set, null set, independent events, discrete random variable, continuous random variable, joint probability density function with 100% accuracy.
 
Can define such terms as sample space, event, singleton, union, intersection, conditional probability, universal set, null set, independent events, discrete random variable, continuous random variable, joint probability density function with at least 80%  accuracy.
 
Can define such terms as sample space, event, singleton, union, intersection, conditional probability, universal set, null set, independent events, discrete random variable, continuous random variable, joint probability density function with less than 80% accuracy.
 
Makes no attempt to define any of the relevant terms.
 
Concepts                                                                                                                                                                                                                                                   
Outcomes
                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    
Can explain such concepts as the classical approach to probability, the frequency approach to probability, permutations, combinations, mean, standard deviation, variance, random variable, mathematical expectation, and generating function with 100% accuracy.
 
Can explain such concepts as the classical approach to probability, the frequency approach to probability, permutations, combinations, mean, standard deviation, variance, random variable, mathematical expectation, and generating function with at least 80% accuracy.
 
Can explain such concepts as the classical approach to probability, the frequency approach to probability, permutations, combinations, mean, standard deviation, variance, random variable, mathematical expectation, and generating function with less than 80% accuracy.
 
Makes no attempt to define any concept.
 
Application                                                                                                                                                                                                                                                
Outcomes
                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    
Can apply set-theoretic ideas to probability problems with 100% accuracy.
 
Can apply set-theoretic ideas to probability problems with at least 80%  accuracy.
 
Can apply set-theoretic ideas to probability problems with less than 80% accuracy.
 
Makes no attempt to apply set-theoretic ideas to probability problems.
 
Whole Artifact                                                                                                                                                                                                                                             
Outcomes
                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    
Can apply the concept of probability to statistics with clear insight.
 
Can apply the concept of probability to statistics with clear some insight.
 
Cannot make any connection between probability and statistics.
 
Makes no attempt to connect probability and statistics.
 
Component                                                                                                                                                                                                                                                  
Outcomes
                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    
Can apply the binomial theorem and binomial coefficients with 100% accuracy.
 
Can apply the binomial theorem and binomial coefficients with 100% accuracy.
 
Can apply the binomial theorem and binomial coefficients with 100% accuracy.
 
Makes no attempt to apply the binomial theorem or binomial coefficients.
 

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Last Updated:8/11/2008 1:01:40 PM