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MA 120 Basic Concepts of Statistics
Greenburg, David S.


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

F2UU 2010 CN

Faculty

Greenburg, David S.

Title

Adjunct Faculty

Degrees/Certificates

Ph.D. Northcentral University
MS The Naval Postgraduate School
BA The CITADEL

Office Hours

30 min prior to and after class, and by appointment.

Daytime Phone

843-729-7828

E-Mail

david.greenburg@park.edu

Semester Dates

18 Oct - 12 Dec 2010

Class Days

--T-R--

Class Time

5:00 - 7:45 PM

Credit Hours

3


Textbook:

Triola, Mario F, Elementary Statistics, 11th Edition, 2010, Addison Wesley. ISBN-10: 0321500245 OR ISBN-13: 9780321500243

Textbooks can be purchased through the MBS bookstore

Additional Resources:

You will need to have access to a scientific calculator. I suggest you use the same calculator throughout the course. Then you will be familiar with it and will avoid having to learn how to use a new calculator at final exam time.

I do not have a brand requirement, but the cost of most brands run about $10 - $20 and can be found in office supply stores or department stores. 

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/.

http://davidmlane.com/hyperstat/
http://www.fgse.nova.edu/edl/secure/stats/index.htm
http://www.cs.gmu.edu/cne/modules/dau/prob/basicprob/basicprob_bdy.html
http://www.basicprobability.com/
http://www.mathgoodies.com/lessons/vol6/intro_probability.html

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

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.
  11. Compute confidence intervals of means and percentages.
  12. Perform hypothesis tests involving one population.
  13. Compute regression and correlation of Bi-variate 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 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 standard normal probability distribution or with 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:
 

Assignment

Possible Points

Total Points

Total %

Midterm Test

100 pts

100

40

Homework

5 sets 10 pts each

50

20

Final Exam

100 pts

100

40

TOTAL

250

250

100

Grading:
 

Assignment

Possible Points

Total Points

Total %

Midterm Test

100 pts

100

40

Homework

5 sets 10 pts each

50

20

Final Exam

100 pts

100

40

TOTAL

250

250

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. 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. 
  • An Accident or Police Emergency.
  • Unforeseen Jury or Witness Duty.
  • Unforeseen Military Deployment or Activation.
  • Funerals for Immediate Family Member (e.g., parents, siblings, grandparents, aunts/uncles, first cousins).

Classroom Rules of Conduct:

Students are expected to act with the dignity and professionalism appropriate for a collegiate academic environment.

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.


Week One.  – Oct 19 – Oct 21

In Chapter 1 we'll learn what the topic of statistics entails. We'll discuss types of data and 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 Chapter 2 we'll learn about frequency distributions, histograms and then we will examine some of the many ways data can be visually displayed graphically.


Week Two.  – Oct 26 – Oct 28
In Chapter 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.


Week Three.  – Nov 2 – Nov 4
In Chapter 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.


Week Four.  – Nov 9 – Nov 11

In Chapter 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.


Week Five.  – Nov 16 – Nov 18
In Chapter 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 Standard Normal distribution. We conclude the unit by learning how the Central Limit Theorem can be applied to sample data sets.


Week Six.  – Nov 23 - Nov 25

In Chapter 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.


Week Seven. – Nov 30 – Dec 2
In Chapter 8 we will examine the basics of hypothesis testing by using one-sample procedures for the hypothesis test of the population mean. 

Week Eight. – Dec 7 – Dec 9

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 you will take the Final Exam and complete 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 2010-2011 Undergraduate Catalog Page 92

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 2010-2011 Undergraduate Catalog Page 92-93

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 2010-2011 Undergraduate Catalog Page 95-96

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 .



Rubric

CompetencyExceeds 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 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. 
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. 

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Last Updated:9/4/2010 7:40:52 PM