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PS 307 Statistics for Social Sci.
Schwartz, Kenneth L.


Mission Statement: Park University provides access to a quality higher education experience that prepares a diverse community of learners to think critically, communicate effectively, demonstrate a global perspective and engage in lifelong learning and service to others.

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

PS 307 Statistics for Social Sci.

Semester

F2T 2012 DL

Faculty

Schwartz, Kenneth L.

Title

Adjunct Faculty

Degrees/Certificates

Licensed Professional Counselor (LPC), State of Texas
M.A., Psychology
B.S., Psychology

Office Location

Online

Office Hours

Online

Daytime Phone

(210) 565-3139

Other Phone

(210) 296-1736

E-Mail

kenneth.schwartz@park.edu

Semester Dates

22 Oct - 16 Dec 2012

Class Days

TBA

Class Time

TBA

Prerequisites

An introductory social science class (i.e., SO141, PS101, CJ100, or SW205) and MA131 or equivalent

Credit Hours

3


Textbook:

Gravetter, F.J. & Wallnau, L.B., (2011) Essentials of Statistics for the Behavioral Sciences, 7th ed Wadsworth, Cengage Learning (ISBN: 10: 0-495-81220-X, ISBN: 13: 978-0-495-81220-3)
 
IBM Statistics 20 Base GradPack available at www.onthehub.com/spss/ (6 month rental).

Huff, D.  (1954/1993).  How to Lie with Statistics, 1993 Reissued Edition.  W. W. Norton & Co. (ISBN: 0-393-31072-8)

 
 

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.
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Course Description:
PS 307 Statistics for Social Sciences: Statistical methods are a primary tool for all of the social and behavioral sciences. This course introduces a wide variety of common statistical techniques and their conceptual bases, including: basic descriptive and inferential statistics, analyses of association and variance, effect sizes, and others in their parametric and nonparametric forms. It provides a background in the relevant theories of provability, sampling, and measurement. And the student will learn how to become a more discerning consumer of statistical information as well as gaining practical experience calculating these statistics by hand and computer. Prerequisites: MA 131 and an introductory social science class (i.e., SO141, PS101, CJ100 or SW 205)

Educational Philosophy:
My education philosophy is that learning requires focused and concentrated effort by a student.  Learning does not just happen.  I see the professor's role to facilitate, clarify, motivate, and provide feedback and guidance that enables a student to accurately assess his or her level of understanding, comprehension, and mastery.  The key to this type of course is to study the concepts, practice the concepts, review the concepts, apply the concepts, and practice the concepts some more.  Learning statistics is much like learning a language.  The more you immerse yourself in the language the more quickly you learn it.  This is not a course that you can succeed at by catching it on the backstroke or trying to catch up.

Class Assessment:
See detailed instructions and rubrics for all assignments in the PS307 course shell at http://parkonline.org.


Core Learning Outcomes

  1. Identify poor statistical reasoning and evaluate the quality of statistical data and the conclusions drawn from it.
  2. Operationalize a theoretical question or practical concern as a testable hypothesis.
  3. Identify the principles of sampling and determine which is appropriate for a given research problem.
  4. Demonstrate the principles of measurement, including index and scale construction, and how those choices guide the application of specific statistical techniques.
  5. Identify and apply the logic and importance of effect size and statistical significance.
  6. Demonstrate an ability to reason from samples to populations, and recognize the limitations of statistical inference.
  7. Interpret and evaluate basic descriptive statistics and correlations.
  8. Apply common parametric and nonparametric statistical techniques.
  9. Demonstrate competency with the general linear model (GLM), including simple and multiple regression, dummy regression, and analysis of variance (ANOVA).
  10. Collect, analyze, and critically evaluate empirical data.
  11. Present research results to specific audiences.



Data Analysis Project: (max. 2500 words, plus tables and figures) Students will be provided with a data set and asked to respond to the following: “tell me everything interesting about these data.”   The essay must include the following components:

1.       A clear hypothesis (or set of related hypotheses) that is defensible and testable, given the available data. This includes identifying each variable, discussing how they are measured and constructed, and how the student hypothesizes their relations.

2.       Calculation and discussion of the descriptive statistics, and direct, part and partial correlations (when relevant), for the chosen variables.

3.       Application of more than one advanced statistical technique (regression or ANOVA variants), including a discussion of effect size and statistical significance), and a comparison of those results.

4.       Analysis of statistical significance for all relevant statistics. Discuss the prospects for generalization from these data.

5.       Critical evaluation of the strengths and weaknesses of the data and their chosen analyses.

6.       Discussion of the practical implications of their findings for real people and policies. Explain how these data might be used, and by whom.

7.       Suggestions for future data collection and analysis that could advance our understanding of their research question beyond what is available through the current data.

In this assignment, the student will be asked to identify patterns in the data, demonstrate competency with appropriate hand and computer-aided calculations, defend their analytical choices, and translate what these numbers mean in plain language. All reasoning and conclusions must be explained and supported through references to specific statistical procedures and results. You will be judged on the quality, clarity, and completeness of your choices, analyses, and presentation.

Rubric

Competency

Exceeds Expectation (3)

Meets Expectation (2)

Does Not Meet Expectation (1)

No Evidence (0)

Analysis & Evaluation                                                                                                                                                                                                                                      
Outcomes
5, 7, 8, 10                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                          

There are at least 5 different well-selected and appropriate statistical techniques (and their results) chosen, justified, and explained 

There are at least 4 different well-selected and appropriate statistical techniques (and their results) chosen, justified, and explained 

There are less than 4 different well-selected and appropriate statistical techniques (and their results) chosen, justified, and explained 



Application                                                                                                                                                                                                                                                
Outcomes
3, 4, 6, 9                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           

All analyses are correctly executed in appropriate detail with no errors. 

Most analyses are correctly executed in appropriate detail with few errors. 

At least two significant or many minor errors. 



Whole Artifact                                                                                                                                                                                                                                             
Outcomes
1, 2, 11                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             

No literacy or numeracy errors and presented in correct format for specified audience. 

Few literacy or numeracy errors and presented in a mostly correct format.  Audience may be ill-defined or inconsistent. 

At least two sifnificant or many minor literacy or numeracy errors and presented in incorrect format for ill-defined or inconsistent audience. 



Core Assessment (250 points = 20%)
The CA is a data analysis project and the take home portion of your final examination.  

Homework Assignments (380 points total = 30.4%): unit problem sets and short answer conceptional and application questions.

Week 1 Homework (60 points = 4.8%)
Week 2 Homework (50 points = 4%)
Week 3 Homework (50 points = 4%)
Week 4 Homework (50 points = 4%)
Week 5 Homework (60 points = 4.8%)
Week 6 Homework (60 points = 4.8%)
Week 7 Homework (50 points = 4%)

Discussion and Participation (50 points x 8 = 400 points = 32%)
Participate in both application and reflection discussions each week, on time and according to instructions, for a possible 25 points each week.

Unit Quizzes (20 points x 7 = 140 points total = 11.2%)
Complete each of the seven multiple choice quizzes on time and according to instructions for a possible 20 points each. Quizzes can be taken one time. There is an optional second quiz each week which you can take to replace your first quiz to improve your score.

Proctored Final Exam (80 points = 6.4%)
Complete the multiple choice section of the final examination on time and according to instructions.

Grading:
Total Points Possible = 1250

A >= 1125
B = 1000-1124
C = 875-999
D = 750-874
F <= 749

See the online course shell for additional details.
All assignments must be submitted through the "Dropbox" in the online course shell for grading.

Late Submission of Course Materials:
 Late work is not accepted.  Assignments must be completed and submitted by the due date.

Classroom Rules of Conduct:
1. Courtesy & Politeness: There is a tendency for people to behave online in ways they would not do in person.  It is essential that everyone treats each other and the professor with respect.

2. Everyone has the right to respect regarding their opinions and feelings.  It's important that students express themselves appropriately (e.g., assertively and not aggressively). Use "I" statements/messages rather than "you."  Use "active listening." Note the links provided in the course shell to information on appropriate communication. Everyone has the right to be listened to without interruption or judgment.

3. It can take a few days to adjust to a course site, so take some time to check out the areas and be patient with yourself and others. After exploring and reading all the information, if you still have questions please post them in the Office area so that other students can benefit from reading them. If you have a personal issue you can email the Professor. The turn around time for responding is a maximum of 48 hours.

4. You will post/discuss study questions in the discussion posting area. In-depth responses are required; "I agree", is not enough.

5. It's best to do assignments in a word processing program and then cut and paste into the discussion area. This way you can save your work in case of a software problem.

6. Have a BACKUP COMPUTER located in case of problems, and do your assignments early enough to provide time for a solution if you have a computer problem. Having a computer problem is not an excuse for not doing an assignment.

Course Topic/Dates/Assignments:
 

 Week

Topic

Due

 1

 How to Lie with Statistics, Essentials

Ch 1- Intro, Ch 2 – Freq Distrib, & Ch 3 – Central Tendency

 Discussion 1, Quiz 1, Homework 1

 2

 Essentials Ch 4 - Variability &

Ch 5 – Z Scores

 Discussion 2, Quiz 2, Homework 2

 3

 Essentials Ch 6 – Probability & Ch 8 – Hypothesis Testing

 Discussion 3, Quiz 3, Homework 3

 4

Essentials Ch 9 – t-Test & Ch 10 – Independent t-Test

 Discussion 4, Quiz 4, Homework 4

 5

 Essentials Ch 12 - Estimation & Ch 16 – Chi Square

 Discussion 5, Quiz 5, Homework 5

 6

Essentials Ch 13 – ANOVA & Ch 14 – Two Factor ANOVA

 Discussion 6, Quiz 6, Homework 6

 7

 Essentials Ch 15 – Correlation & Regression

 Discussion 7, Quiz 7, Homework 7

 8

 Summary & Review- no reading assignment

 Discussion 8,

Final Exam,

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 2011-2012 Undergraduate Catalog Page 95-96

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 2011-2012 Undergraduate Catalog Page 95

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.
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 academically-related 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 course related question, or using any of the learning management system tools.

Park University 2011-2012 Undergraduate Catalog Page 98

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:
This is a challenging course, but you can be successful if you approach it with the proper expectations and focus.  It will require more time than many courses because it is presenting completely new information for many of you.  If you begin the course realizing it will require A LOT of focused study and actually practicing the computational exercises versus just reading and thinking you understand them you will be successful.  It's not a course you can play catch up in nor successfully complete with minimal effort.  The course principles build on each other so falling behind will make the course overwhelming as won't have the sequential understanding needed to build on for the next lesson.

Copyright:

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

Last Updated:9/26/2012 5:03:54 AM