# MA120 Basic Concepts of Statistics

## for S1T 2006

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 120 Basic Concepts of Statistics Semester S2T 2006 DLK Faculty Willcox, John Title Senior Instructor Degrees/Certificates BS MathematicsMA Industrial ManagementMA Logistics Management Office Location Fairchild AFB, WA Office Hours Respond within 48 hours Daytime Phone 509 206 9466 E-Mail John.Willcox@pirate.park.edu johnowx@peoplepc.com Semester Dates 03/13/06  thru 05/08/06 Class Days Monday thru Sunday Class Time 24 hours Prerequisites None Credit Hours 3

Textbook:
Elementary Statistics - 6th Ed by Neil A. Weiss, Addison Wesley Longman ISBN: 0-321-24122-3.  This package includes student access to MathXL and MyMathLab.  These tools include applets that will allow you to complete homework without buying extra statistical software.

Textbooks can be purchased though the MBS bookstore

Textbooks can be purchased though the Parkville Bookstore

Course Description:
A development of certain basic concepts in probability and statistics that are pertinent to most disciplines.  Topics include:  probability models, parameters, statistics and sampling procedures, hypothesis testing, correlation, and regression.  3:0:3

Educational Philosophy:
Each student is responsible for:

o Completing weekly reading assignments.
o Participating in weekly discussions.
o Studying various online resources.
o Preparing two lessons learned
o Completing seven substantial homework assignments.
o Complete five online quizzes with minimum 70%
o Completing a proctored examination during Week 8.

Learning Outcomes:
Core Learning Outcomes

1. Compute descriptive statistics for raw data as well as grouped data
2. Determine appropriate features of a frequency distribution
3. Apply Chebyshev's Theorem
4. Distinguish between and provide relevant descriptions of a sample and a population
5. Apply the rules of combinatorics
6. Differentiate between classical and frequency approaches to probability
7. Apply set-theoretic ideas to events
8. Apply basic rules of probability
9. Apply the concepts of specific discrete random variables and probability distributions
10. Compute probabilities of a normal distribution

Core Assessment:

Description of MA 120 Core Assessment

One problem with multiple parts for each numbered item, except for item #3, which contains four separate problems.

1. Compute the mean, median, mode, and standard deviation for a sample of 8 to 12 data.

2. Compute the mean and standard deviation of a grouped frequency distribution with 4 classes.

3. Compute the probability of four problems from among these kinds or combinations thereof:

a. the probability of an event based upon a two-dimensional table;

b. the probability of an event that involves using the addition rule;

c. the probability of an event that involves conditional probability;

d. the probability of an event that involves the use of independence of events;

e. the probability of an event based upon permutations and/or combinations;

f. the probability of an event using the multiplication rule; or

g. the probability of an event found by finding the probability of the complementary event.

4. Compute probabilities associated with a binomial random variable associated with a practical situation.

5. Compute probabilities associated with either a non-standard normal probability distribution.

6. Compute and interpret a confidence interval for a mean and/ or for a proportion.

Link to Class Rubric

Class Assessment:
Each student is responsible for:

o Completing weekly reading assignments.
o Participating in weekly discussions.
o Studying various online resources.
o Preparing two lessons learned
o Completing seven substantial homework assignments.
o Complete five online quizzes with minimum 70%
o Completing a proctored examination during Week 8.
o A class assessment/rubric will be prepared on each student from the students homework, class participation, quizzes and final examination.

Grading:
• You will be assigned the following assignments.  Relative weights and due dates are included.
Core Assessment/Rubric   64 Points          20.0%
Class Participation      25 Points           7.5%
Homework                 21 Points           6.5%
Lessons Learned           6 Points           2.0%
Quizzes                  80 Points          25.0%
Proctored Final         125 Points          39.0%

Total                   320 Points          100%

You will be able to track your average throughout the course. The grading scale is as follows:

A = 90-100
B = 80-89
C = 70-79
D = 60-69
F = 0-59.

You will be evaluated on the total number of points you earn as compared to the greatest amount of points that may be earned in each course activity. In determining the number of points assigned to an activity, the major factors will be the following questions:

Was the work completed?
Was the work completed correctly?
Was the work completed on time?

Each student is responsible for:

o Completing weekly reading assignments.
o Participating in weekly discussions.
o Studying various online resources.
o Preparing two lessons learned
o Completing seven substantial homework assignments.
o Completing five online quizzes with a minimum score of 70%.
o Completing a proctored examination during Week 8.

Proctored final examination - A final proctored examination will be taken in a proctored testing environment during the 8th week at one of the Park University sites around the country or at an alternative location.  For proctored examinations, photo identification is required at the time of the test.  Guidelines for selecting an acceptable proctor can be found on the Park University Website.
• Other Information on proctored exams:
o It will be the responsibility of the student to arrange for a proctor, by the 6th week of the term, who is accepted and approved by the course instructor.
o Approval of proctors is the discretion of the Online instructor.
o A proctor request form will be made available to you during the first week of class so that you can send your requested proctor to your instructor for approval.
o Failure to take a final proctored exam (or submit your final project for some online graduate courses) will result in an automatic "F" grade.

Late Submission of Course Materials:
• Submission of Late Work: All work should be completed by the end of each course week.  Access to each week will end by the following Friday.  If the student does not complete the work by that following Friday a 0 grade will administered.

Classroom Rules of Conduct:
Online Course Policies: Policy #1:

Submission of Work:

• A class week is defined as the period of time between Monday 12:01 am EST and Sunday at 11:59 PM EST. The first week begins the first day of the term/semester. Assignments scheduled for completion during a class week should be completed and successfully submitted by the posted due date.

• Create a back up file of every piece of work you submit for grading. This will ensure that a computer glitch or a glitch in cyberspace won't erase your efforts.

• When files are sent attached to an email, the files should be in either Microsoft Word, RTF, ASCII, txt, or PDF file formats.

Policy #2: Ground Rules for Online Communication & Participation

• General email: Students should use email for private messages to the instructor and other students. When sending email other than assignments, you must identify yourself fully by name and class in all email sent to your instructor and/or other members of our class.

• Online threaded discussions: are public messages and all writings in this area will be viewable by the entire class or assigned group members.

• Online Instructor Response Policy:  Online Instructors will check email frequently and will respond to course-related questions within 24-48 hours.

• Observation of "Netiquette": All your Online communications need to be composed with fairness, honesty and tact.  Spelling and grammar are very important in an Online course.  What you put into an Online course reflects on your level of professionalism.  Here are a couple of Online references that discuss writing Online

http://goto.intwg.com/ and netiquette http://www.albion.com/netiquette/corerules.html.

• Please check the Announcements area before you ask general course "housekeeping" questions (i.e. how do I submit assignment 3?).  If you don't see your question there, then please contact your instructor.

Policy #3: What to do if you experience technical problems or have questions about the Online classroom.

• If you experience computer difficulties (need help downloading a browser or plug-in, you need help logging into the course, or if you experience any errors or problems while in your Online course, click on the Help button in your Online Classroom, then click on the helpdesk menu item, and then fill out the form or call the helpdesk for assistance.

• If the issue is preventing you from submitting or completing any coursework, contact your instructor immediately.

Course Topic/Dates/Assignments:
You have heard Benjamin Disraeli's assertion: "There are three types of lies:  lies, damned lies, and statistics."  By learning the concepts expressed in this course, you should be able to sort out how the information in collections of data is interpreted (as well as misinterpreted).  Each week we'll focus on different aspects of the general properties of data sets,  methods of collecting data, ways of analyzing and expressing ideas about data sets, and problem-solving methods based on information contained in our text, Elementary Statistics (6th ed), by Neil Weiss (Addison-Wesley) ISBN: 0-321-24122-3.

During Week 1, we begin to learn the language of statistics and examine some basic sampling and experimental design strategies.  We will also learn strategies for organizing data, and representing data sets in graphs and charts.  Discussion of analysis of graphical representations of data will allow us to classify what type of distribution represents a particular data set.  We will also learn how mistakes in constructing graphs improperly causes data to be misrepresented.  Our online discussions will help you become familiar with the online environment, learn what we hope to achieve from this course, understand my general guidelines and expectations, and assess your interest in the the study of statistics.

During Week 2, we will examine basic calculations used in descriptive statistics including: measures of center, sample mean, and sample standard deviation.  We will also discuss descriptive measures for populations, including the use of samples.  We will continue discussing basic tools for descriptive statistics, including the use of linear regression and linear correlation.

During Week 3, we will learn what probabilities are and learn some of the basic rules of probability.  We will also learn about discrete random probabilities and probability distributions.

During Week 4, we will learn about the normal distribution, areas under the standard normal curve, and working with normally distributed variables.  We will also examine sampling error, the need for sampling distributions and and learn how to apply the sampling distribution of the sampling mean.

During Week 5, we begin an examination of  inferential statistics.  We begin with a discussion of confidence intervals for one population mean.  We will also start to examine the basics of hypothesis testing.

During Week 6, we continue to examine hypothesis testing for one population mean.  We will then turn our attention to the inferential statistics of two population means.

During Week 7, we will examine the inferential statistics of population proportions and analysis of variance using one-way ANOVA.

During Week 8, we will conclude our examination of topics in statistics by learning how to use the Chi-square distribution to determine goodness of fit and to determine if there is an association between two variables.  We will also complete the proctored examination during this week.

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 2005-2006 Undergraduate Catalog Page 85-87

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 2005-2006 Undergraduate Catalog Page 85-87

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 "WH".
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.
ONLINE NOTE: An attendance report of "P" (present) will be recorded for students who have logged in to the Online classroom at least once during each week of the term. Recording of attendance is not equivalent to participation. Participation grades will be assigned by each instructor according to the criteria in the Grading Policy section of the syllabus.

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. Park University is committed to meeting the needs of all learners that meet the criteria for special assistance. These guidelines are designed to supply directions to learners 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 American with Disabilities Act of 1990, regarding learners with disabilities and, to the extent 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

 Competency Exceeds Expectation (3) Meets Expectation (2) Does Not Meet Expectation (1) No Evidence (0) Synthesis                                                                                                                                              Outcomes Can compute and interpret a confidence interval for a sample mean for small and large samples, and for a proportion with 100% accuracy. Can compute and interpret a confidence interval for a sample mean for small and large samples, and for a proportion with at least 80% accuracy. Can compute and interpret a confidence interval for a sample mean for small and large samples, and for a proportion with less than 80%  accuracy. Makes no attempt to compute or interpret a confidence interval. Analysis                                                                                                                                               Outcomes Can apply the normal distribution, Central limit theorem, and binomial distribution to practical problems with 100% accuracy. Can apply the normal distribution, Central limit theorem, and binomial distribution to practical problems with at least 80% accuracy. Can apply the normal distribution, Central limit theorem, and binomial distribution to practical problems with less than 80% accuracy. Makes no attempt to apply the normal distribution, Central Limit Theorem, or binomial distribution. Evaluation                                                                                                                                             Outcomes Can perform and interpret a hypothesis test with 100% accuracy. Can perform and interpret a hypothesis test with at least 80% accuracy. Can perform and interpret a hypothesis test with less than 80% accuracy. Makes no attempt to perform a test of hypothesis. Terminology                                                                                                                                            Outcomes Can explain event, simple event, mutually exclusive events, independent events, discrete random variable, continuous random variable, sample,  and population with 100% accuracy. Can explain event, simple event, mutually exclusive events, independent events, discrete random variable, continuous random variable, sample,  and population with at least 80% accuracy. Can explain event, simple event, mutually exclusive events, independent events, discrete random variable, continuous random variable, sample,  and population with less than 80% accuracy. Makes no attempt to explain any of the terms listed. Concepts                                                                                                                                               Outcomes Can explain mean, median, mode, standard deviation, simple probability, and measures of location with 100% accuracy. Can explain mean, median, mode, standard deviation, simple probability, and measures of location with at least 80% accuracy. Can explain mean, median, mode, standard deviation, simple probability, and measures of location with less than 80%  accuracy. Makes no attempt to define any concept. Application                                                                                                                                            Outcomes Compute probabilities using addition multiplication, and complement rules and conditional probabilities. Compute statistical quantities for raw and grouped data. Compute probabilities using combinatorics, discrete random variables, and continuous random variables. All must be done with 100% accuracy. Compute probabilities using addition multiplication, and complement rules and conditional probabilities. Compute statistical quantities for raw and grouped data. Compute probabilities using combinatorics, discrete random variables, and continuous random variables. All must be done with at least 80% accuracy. Compute probabilities using addition multiplication, and complement rules and conditional probabilities. Compute statistical quantities for raw and grouped data. Compute probabilities using combinatorics, discrete random variables, and continuous random variables. All are done with less than 80% accuracy. Makes no attempt to compute any of the probabilities or statistics listed. Whole Artifact                                                                                                                                         Outcomes Can apply the concepts of probability and statistics to real-world problems in other disciplines with 100 % accuracy. Can apply the concepts of probability and statistics to real-world problems in other disciplines with at least 80 % accuracy. Can apply the concepts of probability and statistics to real-world problems in other disciplines with less than 80% accuracy. Makes no attempt to apply the concepts to real-world problems. Component                                                                                                                                              Outcomes Can use a calculator or other computing device to compute statistics with 100% accuracy. Can use a calculator or other computing device to compute statistics with at least 80% accuracy. Can use a calculator or other computing device to compute statistics with less 80% accuracy. Makes no attempt to use any computing device to compute statistics. M/LL Courses                                                                                                                                           Outcomes

Copyright:

This material is copyright and can not be reused without author permission.

Last Updated:4/13/2006 6:54:50 PM