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SO 307 Statistics for Social Sci.
Handelman, Lori D.


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

SO 307 Statistics for Social Sci.

Semester

S1T 2011 DLC

Faculty

Handelman, Lori D.

Title

Adjunct Faculty

Degrees/Certificates

PhD in Psychology, The University of Texas at Austin (2003)
MA in Psychology, The University of Texas at Austin (2003)
BA in Psychology, University of Arkansas at Fayetteville (1998)

Office Location

New York, NY

Office Hours

MWF 9-10am, or by appointment

E-Mail

lori.handelman@park.edu

ldhandelman@gmail.com

Semester Dates

Monday, January 10, 2011 to Sunday, March 6, 2011

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:
Healey, J. (2009). Statistics: A Tool for Social Research, 8th ed. Thomson Learning-Wadsworth.
(Bundled by MBS with SPSS 16.0 Student Edition & SPSS Guide.)

Huff, D.  (1954/1993).  How to Lie with Statistics, 1993 Reissued Edition.  W. W. Norton & Co.

Textbooks can be purchased through the MBS bookstore

Textbooks can be purchased through the Parkville Bookstore

Additional Resources:
Additional Readings as necessary.

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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FAQ's for Online Students - You might find the answer to your questions here.


Course Description:
SO 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:

I believe material is best learned by active engagement, and by applying it to your own lives. Whenever possible, I will encourage you to use examples from your life, or from material you learn or read in other courses. Taking an online course requires a lot of you, so you should consider it one of your most important tasks for this semester. It can be disorienting, working alone without the support of classmates, so I strongly encourage you to communicate with me directly if you are ever unsure about anything at all. I will be delighted to help you in any way I can.

Learning Outcomes:
  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.


Core Assessment:

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.

Link to Class Rubric

Class Assessment:
See detailed instructions and rubrics for all assignments in the SO307 course shell at http://parkonline.org.

Core Assessment (200 points = 20%)
The CA is a small data analysis project and the take home portion of your final examination.

Pre-Test (30 points = 3%): timed online multiple-choice quiz of algebraic proficiency.

Regular Assignments (380 points total = 38%): unit problem sets and short answer conceptional and application questions.
Unit 1 Assignment (80 points = 8%)
Unit 2 Assignment (60 points = 6%)
Unit 3 Assignment (60 points = 6%)
Unit 4 Assignment (60 points = 6%)
Unit 5 Assignment (60 points = 6%)
Unit 6 Assignment (60 points = 6%)

Discussion and Participation (25 points x 8 = 200 points = 20%)
Participate in all 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 = 14%)
Complete each of the seven multiple choice quizzes on time and according to instructions for a possible 20 points each.

Proctored Final Exam (50 points = 5%)
Complete the multiple choice section of the final examination on time and according to instructions.

Grading:
Total Points Possible = 1000

A >= 900
B = 800-899
C = 700-799
D = 600-699
F <= 599

See attached file (2008Rubric.pdf) and 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:

You are expected to submit all your materials by the stated deadlines. If you see that you will be unable to meet a deadline, I expect you to communicate with me in advance of the deadline. Things happen - life interferes, computers crash, internet connections fail - so you should plan ahead. Save everything multiple times in multiple places. Work ahead when possible so you are not caught off guard by these kinds of events. I may make accommodations for extreme circumstances, but I require that you discuss these with me as early as possible beforehand.

Classroom Rules of Conduct:

This is a professional classroom, and you are expected to engage each other with civility and curiosity. Substantive comments are expected, and if you disagree with someone, you should explain your disagreement with reference to the material being studied. Violations of these rules of conduct will not be tolerated.

Course Topic/Dates/Assignments:

 Week Topic
Due
 1  Speaking Statistics
 Pre-quiz, Quiz 1
 2  Descriptive Statistics
 Quiz 2, Assignment 1
 3  Probability & Inference
 Quiz 3, Assignment 2
 4  Statistical Significance
 Quiz 4, Assignment 3
 5  Statistical Association I
 Quiz 5, Assignment 4
 6 Statistical Association 2   Quiz 6, Assignment 5
 7  Multivariate Analysis
 Quiz 7, Assignment 6
 8  Summary & Review
 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 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
Writing in the social sciences - and this includes writing about statistical information - involves the discussion of others' work! Therefore, it is expected that you will be quoting or summarizing from something already written, or published. In every instance, proper attribution (including the full citation) and proper indications of quotation are absolutely required. Failure to do so will result in disciplinary action. If you are ever uncertain, please ask me in advance, and I will be happy to help you.

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: 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.

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 .


Attachments:
syllabus

Rubric

CompetencyExceeds 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.  

Copyright:

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Last Updated:12/28/2010 10:11:19 AM