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Course  MA 120 Basic Concepts of Statistics 
Semester  S1F 2011 QU 
Faculty  Wakelin, Michael L. 
Title  Adjunct Faculty 
Degrees/Certificates  MBA B.S. Management ASQ: Certified Reliability Engineer 
Daytime Phone  5712124163 
Other Phone  FAX: 7035628404 
EMail  Michael.Wakelin@park.edu 
 mlwakelin@att.net 
Semester Dates  S1F 2011 TERM DATES: 30 May â€“ 31 July 2011 
Class Days  M 
Class Time  5:30  10:30 PM 
Credit Hours  3 
Textbook:
Required Text: Elementary Statistics 11th Edition
Mario F. Triola
ISBN10: 0321500245
ISBN13: 9780321500243
Highly Suggested: By Milton F. Loyer

ISBN10: 0321570626
ISBN13: 9780321570628
Published by AddisonWesley
© 2010 Pub. Date: Jan 6, 2009
Format: Paper



PLEASE NOTE: The Instructor expects the Student to acquire one of the calculators within the The Coveted Calculator 101 and the Coveted Calculator 102. These two PDFs are as attachments to this Syllabus.
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.
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 8009273024
Resources for Current Students  A great place to look for all kinds of information http://www.park.edu/Current/.
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. 3:0:3Learning 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:
Class Meeting

Chapters

Activities

Assignments Due Today

May 30^{th}

1, 2, & 3

Lecture
Chapter 2 & 3

Email Definitions (Chapter 1): Population, Sample,
Parameter, Statistic, Discrete Data, Continuous
Data,
Voluntary Response Sample, Random Sample, and
Simple Random Sample, to
your Instructor!

June 6^{th}

4

Lecture
Chapter 4

Read
Chapter 4: Sections 41, 42, 43, 44, 45, & 47
DO Section
22: #6, #14, #18
DO Section
23: #10
DO Section
32: #8, #12, #30, & #32
DO Section
3.3: #6, #18, #30, & #36
DO Section 34: #10

June 13^{th}

5

Lecture Chapter 5

Read
Chapter 5: Sections 51, 52, 53, & 54
DO Section
42: #14, #18, #26, & #28
DO Section
43: #20, #28, & #30
DO Section
44: #10, #16, & #18
DO Section
45: #16 & #24
DO Section
47: #10, #14, #16, & #22

June 20^{th}

6

Lecture Chapter 6

Read
Chapter 6: Sections 61, 62, 63, 65
Quiz
Chapter 2 & 3
DO Section
52: #8, #10, #12, & #16
DO Section
53: #16, #18, #26, & #28
DO Section
54: #8, #10, #12, & #18

June 27^{th}

7

Lecture Chapter 7

Read Chapter
7: Sections 71, 72, 73, 74
Quiz
Chapter 4
DO Section
62: #10, #12, #14, #16, #18, & #20
DO Section
63: #8, #10, #12, #14, #22, & #24
DO Section
65: #8, #9, #10, & #12,

July 4^{th}

8

Lecture Chapter 8

Read
Chapter 8: Sections 81, 82, 83, 85
Quiz
Chapter 5
DO Section
72: #8, #10, #12, #24,& #30
DO Section 73: #10, #14, & #22
DO Section 74: #8, #18, #20, & #22

July 11^{th}

10

Lecture Chapter 10

Read Chapter 10: Sections 101, 102, 103
Quiz Chapter 6
DO Section 82: #10, #12, & #14,
DO Section 83: # 6, #10, & #14
DO Section
85: # 6, #8, #10, #12, & #16

July 18^{th}

Core Review

Core Review

Quiz Chapter 7
DO Section 102: #6, #8, #10, #12
DO Section 103: #6, #8, #10, #12,

July 25^{th}

Core

Core Assessment

Quiz Chapter 8

Grading:
First off, I expect that ALL STUDENTS will read the Chapters PRIOR to my class! This is imperative!
Secondly, the final course grade will be determined using the following measurements:
Homework: 20%
Quizzes: 38%
Core Assessment: 40%
Class Participation: 2%
Total: 100%
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. For every week that one homework assignment is late, 10% of the grade will be deducted.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. If a online quiz or take home quiz is given and turned in late, a zero will be submitted as the grade.
 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:
I expect that ALL STUDENTS will read the Chapters PRIOR to my class! This is imperative!
Class Participation is expected and will form a part of the final grade. Students are expected to attend all classes and be on time. Roll will be checked each class meeting. Classes missed for legitimate reasons, such as illness, temporary duty, are excusable; however, the student must notify the instructor (prior to the class to be missed if possible) and make up the missed work as follows:
o Read and be responsible for assigned readings/course content;
o If a test is to be missed it must be taken before the scheduled test date.
o If this is impossible, it must be taken before the class begins the week following the scheduled test date or a grade of zero (0) will be assigned for that exam.
o It is the student's responsibility to contact the instructor and arrange to take the test.
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 Week 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 addition, 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. Lastly, 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 Week 2 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 Week 3 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 Week 4 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 Week 5 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 Week 6 we will examine the basics of hypothesis testing by using onesample procedures for the hypothesis test of the population mean.
In Week 7 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.
In Week 8, we will do a thorough review of the course and prepare for the Core Assessment.
In Week 9, we will administer and complete the Core Assessment.
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 20102011 Undergraduate Catalog Page 92
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Academic dishonesty includes committing or the attempt to commit cheating, plagiarism, falsifying academic records, and other acts intentionally designed to provide unfair advantage to the students.
Cheating includes, but is not limited to, intentionally giving or receiving unauthorized aid or notes on examinations, papers, laboratory reports, exercises, projects, or class assignments which are intended to be individually completed. Cheating also includes the unauthorized copying of tests or any other deceit or fraud related to the student's academic conduct.
Falsifying academic records includes, but is not limited to, altering grades or other academic records.
Other acts that constitute academic dishonesty include:
Stealing, manipulating, or interfering with an academic work of another student or faculty member.
Collusion with other students on work to be completed by one student.
Lying to or deceiving a faculty member.
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 20102011 Undergraduate Catalog Page 9293
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ALL GRADED WORK FOR THIS COURSE MUST BE YOUR OWN. YOU ARE NOT TO RECEIVE OUTSIDE ASSISTANCE FROM ANYONE OTHER THAN YOUR INSTRUCTOR. To further clarify; classmates, spouses, coworkers, tutors, clergy, librarians, friends, relatives, and pets are included as OUTSIDE ASSISTANCE. PLEASE DO NOT VIOLATE THIS RULE.
When discussion questions request you to answer in your own words, do not copy words from the textbook as your own. State YOUR understanding of the concept, not the understanding of some other person. If you are allowed to quote the textbook, or other sources, you must use proper quotation markings and declare the source including web URL address or book page number from which you copied the text. Not following these rules constitutes plagiarism, and will not be tolerated. (This means you will not earn points for the assignment, and if the plagiarism does not stop immediately you will FAIL the course. Additionally, a report of the incidence will be sent to your permanent academic file.)
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.
Park University 20102011 Undergraduate Catalog Page 9596
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 .
Attachments:
The Coveted Calculator 101
The Coveted Calculator 102
The Coveted Calculator 101
The Coveted Calculator 102
The Coveted Calculator 101
The Coveted Calculator 102
The Coveted Calculator 101
The Coveted Calculator 102
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:
This material is protected by copyright and can not be reused without author permission.Last Updated:5/9/2011 11:01:15 PM