MA120 Basic Concepts of Statistics
for S1T 2012
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Vision Statement: Park University, a pioneering institution of higher learning since 1875, will provide leadership in quality, innovative education for a diversity of learners who will excel in their professional and personal service to the global community.
Course  MA 120 Basic Concepts of Statistics 
Semester  S1T 2012 DLF 
Faculty  Green, Kathleen R. 
Title  Adjunct Instructor 
Degrees/Certificates  PhD  Adult Education MBA  Business Administration BA  Chemistry 
Office Location  See the OFFICE tab in the Course Home Menu 
Office Hours  9am  5pm Mountain Time Monday  Friday 
Other Phone  4802475574 (FAX) 
EMail  Kathleen.Green@park.edu 
Semester Dates  S1T 2012 
Class Days  TBA 
Class Time  TBA 
Credit Hours  3 
Textbook:
Your lab fee for MyMathLab includes the ebook version of the textbook.
If you wish to have a hardcopy version of the text in addition to the ebook you may order it from MBS, the Park online bookstore at http://direct.mbsbooks.com/park.htm.
OPTIONAL:
Hardcopy Text: Elementary Statistics, 11th Ed. w/Multimedia Study Guide
Author: Mario F. Triola
Publisher: AddisonWesley
ISBN: 9780321500243
Textbooks can be purchased through the MBS bookstore
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 8002704347.
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FAQ's for Online Students  You might find the answer to your questions here.
Course Description: MA120 Basic Concepts of Statistics (GE): A development of certain basic concepts in probability and statistics that is pertinent to most disciplines. Topics include: probability models, parameters, statistics and sampling procedures, hypothesis testing, correlation and regression. 3:0:3
Educational Philosophy:
My educational philosophy is one of interactiveness based on lectures, readings, dialogues, examinations, internet, videos, web sites and writings. I will engage each student to encourage the lively exploration of ideas, issues, and contradictions. School should be fun not a chore. Anyone who works at it with diligence and courage can learn to think more clearly, accurately, and efficiently and express ideas with clarity and poise.
Learning Outcomes:
Core Learning Outcomes
 Compute descriptive statistics for raw data as well as grouped data.
 Determine appropriate features of a frequency distribution.
 Apply Chebyshev's Theorem.
 Distinguish between and provide relevant descriptions of a sample and a population.
 Apply the rules of combinatorics.
 Differentiate between classical and frequency approaches to probability.
 Apply settheoretic ideas to events.
 Apply basic rules of probability.
 Apply the concepts of specific discrete random variables and probability distributions.
 Compute probabilities of a normal distribution.
 Compute confidence intervals of means and percentages.
 Perform hypothesis tests involving one population.
 Compute regression and correlation of Bivariate data.
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 there of:
a. the probability of an event based upon a twodimensional 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 standard normal probability distribution or with a nonstandard normal probability distribution.
6. Compute and interpret a confidence interval for a mean and/ or for a proportion.
Link to Class Rubric
Class Assessment:
THE COURSE LEARNING ACTIVITIES
Introductions  By the end of the first week of the course submit a short paragraph to introduce yourself, and respond to someone else's introduction
Each week you will have these regular learning activities:
Reading – Read the assigned chapter sections in your textbook
Lecture – Read the Content Lecture Files contained within the course
Media  View videos, flash files, and PowerPoint presentations
Webliography  Enhance the learning experience with varying presentations and examples of the weekly topics beyond the course lectures, textbook, and MyMathLab
Discussions  Answer one question for each week, and post a response to someone else's answer (graded activity). Student MUST follow the directions provided to obtain full credit.
Homework  Complete the MyMathLab weekly homework assignment (graded activity)
Quiz  Complete the MyMathLab weekly quiz (graded activity)
Final Exam  Complete the final exam in week 8 (graded activity)
Grading:
Grading:
Assignment

Possible Points

Total Points

Total %

Introduction 
5 pts 
5

0.9

Introduction Response

5 pts 
5

0.9

Discussion Answer

10 pts each

80

13.7

Discussion Response 
5 pts each 
40

6.8

Homework 
15 pts each 
120

20.5

Quiz

20 pts each

160

27.4

Final Exam

175 pts

175

29.9

TOTAL


585


Letter Grade
Letter

Number of Points

Percentage

A

524  585

89.5  100%

B

466  523

79.5  89.4%

C

407  465

69.5  79.4%

D

349  406

59.5  69.4%

F

000  348

00  59.4%

Late Submission of Course Materials:
It is unfair to other students to allow some individuals to submit assignments after the scheduled due date. Therefore, all assignments are expected to be completed by set deadlines. An exception to the rule is a 24 hour extension provided only for thread postings; but using it will mean you will be assessed with a 50% penalty on earned points for the assignment. The only other considerations for allowable late assignments are limited to the following valid list of emergency reasons. Please note even these reasons are only acceptable at the discretion of your instructor.
 A medical emergency or a serious acute illness. All medical emergencies and illnesses must be verified by a note on letterhead by an M.D., D.O., P.A., or R.N. I will not normally accept a note from other health professionals (e.g., Ph.D., MSW, D.C., Physical Therapist) because their professional functions rarely involve medical emergencies or acute illnesses. I will accept late work for students who can provide evidence of a verified medical emergency (but not acute illness) involving a child, spouse, parent, sibling, or grandparent.
 An Accident or Police Emergency. I will require an accident report or note on letterhead from an appropriate law enforcement officer to accept late work due to accidents or police emergencies (e.g., assault on student, student taken hostage, detained witness of a crime).
 Unforeseen Jury or Witness Duty. I will require a note on letterhead from a judge or attorney stating you had no advance notice of duty to accept late work due to jury or witness duty.
 Unforeseen Military Deployment or Activation. I will require a note on official letterhead from your commanding officer stating you had no advance notice of deployment or activation.
 Funerals for Immediate Family Member (e.g., parents, siblings, grandparents, aunts/uncles, first cousins). I will require a copy of the obituary or a note from a minister or funeral director.
Classroom Rules of Conduct:
Computer literacy is expected: You are expected to have sufficient access to a personal computer with a modem and web browser, access to the Internet, and to use your PIRATEMAIL email account.
Please do not request special allowances if you do not have a way to access the course or your PIRATEMAIL.
Policy #1: Submission of Work.
A class week is defined as the period of time between Monday 12:01 AM MT and Sunday at 12:00 AM MT. (MT is Mountain Time at Denver, Colorado, where eCollege is located. When Denver is in Daylight Saving Time, the course will be also. Please make sure you adjust your classwork schedule to meet the MT deadlines.) The assignments scheduled for completion during a class week should be completed and successfully submitted by the posted due date.
NO EXTENSIONS WILL BE MADE FOR MISSED DEADLINES.
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 as email, thread, or dropbox attachments, they should be in either Microsoft Word, Microsoft Works, RTF, ASCII, txt, pdf, JPEG, or TIFF file formats. WORDPERFECT and some scanner files (like .max) are not acceptable for this course.
Policy #2: Ground Rules for Online Communication & Participation.
Journal: You should use this communication tool for private messages to me. Make sure you choose the option to allow me to view your entry. Should you need to send me an attachment of your work, you will need to send it via an email.
General email: You should use email for private messages to me and your classmates. When sending me an email, you must identify yourself fully by course number, section letters, and last name in the SUBJECT LINE of your email: MA120 DL, your last name. PLEASE DO THIS ON EVERY EMAIL THROUGHOUT THE ENTIRE TERM.
Threaded discussions: are public messages and all writings in this area will be viewable by the entire class.
Instructor Response Policy: I am required to check my email frequently and respond to courserelated questions within 2448 hours. Seldom a day goes by that I am not reading and responding to emails and thread postings.
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.
I only accept professional postings.
PROOFREAD AND USE THE SPELLCHECK TOOL FOR ALL THREAD POSTINGS.
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 plugin, 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. (I HIGHLY SUGGEST YOU JOT DOWN THE PHONE NUMBERS OF ECOLLEGE AND PARK HELPDESK FROM THE WEBSITES NOW. In case you cannot enter the course or Park websites later you will have the numbers to call.)
Course Topic/Dates/Assignments:
This course provides an introduction to the world of statistical analysis. Each week we'll focus on different aspects of the general topic.
In Unit 1 we'll learn what the topic of statistics entails. We'll discuss some ways to collect the needed data for a statistical study. By the end the unit we'll have a view of how the two distinct divisions of statistics, descriptive and inferential, are related.
In Unit 2 we'll discover how to convert pure data into corrupted data, also referred to as ungrouped data into grouped data. Then we will examine some of the many ways data can be visually displayed graphically.
In Unit 3 we will examine ways to describe data by looking at its central tendency, its variation from its center, and how to determine the location of an element within a data set. A method of finding the proportions of variation a data set possesses will also be covered.
In Unit 4 we'll explore the basic concepts of probabilities, the branch of mathematics that allows us to take a sample and make predictions about the population from which it was derived. We'll strive to gain a fundamental understanding of probability through its addition, multiplication and counting rules.
In Unit 5 we combine the probability concepts and the statistical concepts we previously learned to construct discrete probability distributions. Then we'll learn how to find statistics of the distribution. The unit ends with a discussion on a specific discrete probability distribution called the binomial distribution.
In Unit 6 the discussion changes from discrete distributions to continuous random variable distributions. We begin looking at the Normal distribution and then quickly moving on the the Standard Normal distribution. We conclude the unit by learning how the Central Limit Theorem can be applied to sample data sets.
In Unit 7 we move into inferential statistics. We learn how to use a sample mean to estimate the population mean, and how we can confidently report its value within a specific interval.
In Unit 8 we will examine the basics of hypothesis testing by using onesample procedures for the hypothesis test of the population mean. In addition we will conclude our examination of topics in statistics by discussing the purpose of regression and correlation analysis. First, we'll examine some introductory terms, then focus on simple linear regression analysis and simple linear correlation analysis.
During this final week of the course you will also complete the proctored Final Exam and the Course Evaluation.
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 students and faculty members are encouraged to take advantage of the University resources available for learning about academic honesty (www.park.edu/current or http://www.park.edu/faculty/).from Park University 20112012 Undergraduate Catalog Page 93
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. from Park University 20112012 Undergraduate Catalog Page 93
Attendance Policy:
Instructors are required to maintain attendance records and to report absences via the online attendance reporting system.
 The instructor may excuse absences for valid reasons, but missed work must be made up within the semester/term of enrollment.
 Work missed through unexcused absences must also be made up within the semester/term of enrollment, but unexcused absences may carry further penalties.
 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".
 A "Contract for Incomplete" will not be issued to a student who has unexcused or excessive absences recorded for a course.
 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.
 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: Students must participate in an academically related activity on a weekly basis in order to be marked present in an online class. Examples of academicallyrelated activities include but are not limited to: contributing to an online discussion, completing a quiz or exam, completing an assignment, initiating contact with a faculty member to ask a courserelated question, or using any of the learning management system tools.
Park University 20112012 Undergraduate Catalog Page 96
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 .
Additional Information:
INCOMPLETE POLICY
Incompletes are NOT a right, but a rare exception that are granted only in the most extraordinary of situations.
If you feel that you will require an incomplete (again, the exception, not the rule), it is your responsibility to contact your instructor BEFORE THE END OF THE COURSE and make this request. In most cases, written third party documentation will be required to support your request. It is at the discretion of the instructor whether an incomplete will be granted and for what length of time it will be granted, with an absolute maximum extension period of 90 days. Furthermore, incomplete grades will be assigned following all the requirements indicated by the Park University Incomplete Policy.
Click here to view Park University's Incomplete Policy
Bibliography:
I began teaching and tutoring for Park University at the Mountain Home AFB, Idaho Campus in 1993. Until April 31, 2005, I was also the Testing Center Supervisor for LaserGrade Computerized Testing (Yes, one of those "official" proctors). I watched the Park University Online Program grow from a handful of instructors and students to its present day size. As an online instructor I have been required to take several online instructional courses, and have also received my PhD in Adult Education, specializing in Online/Distant Learning. I have developed many courses in various fields of study, for example: Advanced Aerodynamics, Algebra, Statistics, and Accounting, just to name a few. So you might say I have experienced the online program from the viewpoint of a student, a proctor, an instructor, course developer, and in a limited way, an administrator! During the continual growth period there have been numerous changes and improvements. Please read more about me in my introduction posting.
I pledge to do my best as your instructor. Will you do the same as my student? If so, let's work together and hopefully we will all learn something new.
Kathleen Green
Rubric
Competency  Exceeds Expectation (3)  Meets Expectation (2)  Does Not Meet Expectation (1)  No Evidence (0) 
Evaluation Outcomes 10  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. 

Synthesis Outcomes 10  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 10  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. 

Terminology Outcomes 4,5,7  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 1,6  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 1,2,3,8,9  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 7,8  Can apply the concepts of probability and statistics to realworld problems in other disciplines with 100 % accuracy.  Can apply the concepts of probability and statistics to realworld problems in other disciplines with at least 80 % accuracy.  Can apply the concepts of probability and statistics to realworld problems in other disciplines with less than 80% accuracy.  Makes no attempt to apply the concepts to realworld problems. 

Components Outcomes 1  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. 
Copyright:
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and can not be reused without author permission.
Last Updated:12/28/2011 10:00:05 AM