SO307 Statistics for Social Sci.

for S2D 2011

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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.


SO 307 Statistics for Social Sci.


S2D 2011 DA


Wright, Barbara May


Adjunct Faculty


BA psychology major, math minor
MA clinical psychology with specialization in school psycholgy

Office Location


Office Hours


Daytime Phone

(520) 624-4690

Other Phone

(520) 548-6209


Semester Dates

03/14/11 through 05/08/11

Class Days


Class Time

1:30 - 7:00 PM


MA 131 and introduction to a social science class(i.e. SO 141, PS 101, CJ 100 or SW 205)

Credit Hours


Healey, J.  (2009)  Statistics:  A Tool for Social Research - 8th Edition. Thomas Learning-Wadsworth.
       ISBN:  0495096555
Huff, D.  (1954/1993)  How to Lie with Statistics - 1993 Reissued Edition.  Norton & Co.
       ISBN:   0393310728

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 800-270-4347.
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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 will work with you to learn statistics by encouraging the use of positive learning experiences while maintaining the high standard of ethical behavior within the classroom.  I desire to see you succeed and will use various techniques which encourage positive learning through lectures, homework assignments, participation, and project experiences while positively studying and preparing for the tests.

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:
The breakdown of the class activities includes the following:
Pretest:  25 points (2.5%)
Discussion & Participation:  20 points x 8 classes  =  160 points  (16%)
Quizzes:  7 @ 50 points each  =  350 points  (35%)
Assignments # 1 - #7:  7 @ 25 points each  =  175 points  (17.5%)
Final:   90 points  (9%)
Core Assessment:  200 points  (20%)

Maximum Points Possible:  1000
A  =  900  -  1000
B  =  800  -  900
C  =  700  -  799
D  =  600  -  699
F  =  Below 600

Late Submission of Course Materials:
Generally, I do not accept late work.  However, if there is an emergency, please discuss it with me as soon as possible so that consideration can be taken into account.  I would prefer that you discuss it with me prior to the due date or immediately after that date.

Classroom Rules of Conduct:
Consideration should be given to all rules that are followed as noted in the references in school policy and procedures so that there is a maintaining of high standards of ethical behavior within the classroom

Course Topic/Dates/Assignments:
Lectures indicate what will be covered on each states date.  Quizzes will happen at the start of the class, prior to lectures, on the date notes.  Assignments are indicated for what is due the following week following the given lectures. 
Class activities and assignments include the following:
03/19/11:   Introductions  -  Approaching Stats Positively  -  Prologue
                  Chapter 2:  Basic Descriptive Statistics
                  Chapter 3:  Central Tendency, Dispersion, Normal Curve
                        WORK:   Prequiz
                                        Assignment #1:  Chapter 2:  Problems  2.1, 2.2, 2.5, 2.9, 2.11
                                                                 Chapter 3:  Problems  3.3, 3.5, 3.7, 3.10, 3.12, 3,14
03/26/11:  Chapter 4:  Measures of Dispersion
                 Chapter 5:  Normal Curve
                         WORK:  Quiz 1
                                        Assignment #2:  Chapter 4:  Problems  4.4, 4.8, 4.11
                                                                 Chapter 5:  Problems  5.2, 5.3, 5.5, 5.8, 5.9, 5.11, 5.12
04/02/11:  Chapter 6:  Sampling
                 Chapter 7:  Estimation Procedures
                 Chapter 8: Hypothesis Testing - One Sample Case
                        WORK:  Quiz 2
                                      Assignment #3:  Chapter 6:  Problem  6.1
                                                               Chapter 7:  Problems  7.1, 7.3, 7.4, 7.10, 7.13
                                                               Chapter 8:  Problems  8.1, 8.4, 8.5, 8.9, 8.11
04/09/11:  Chapter 9:  Hypothesis Testing - Two Sample Case
                 Chapter 10:  Hypothesis Testing - The Analysis of Variance
                        WORK:  Quiz 3
                                       Assignment #4:  Chapter 9:  Problems  9.1, 9.3, 9.7, 9.11, 9.13
                                                                Chapter10:  Problems  10.1, 10.3, 10.5, 10.7
04/16/11:  Chapter 11:  Hypothesis Testing - Chi Square
                 Chapter 12:  Bivariate Association
                        WORK:  Quiz 4
                                       Assignment #5:  Chapter 11:  Problems  11.2, 11.3, 11.9, 11.11, 11.17
                                                                Chapter 12:  Problems  12.1, 12.3, 12.9
04/23/11:  Chapter 13:  Association at Nominal Level
                 Chapter 14:  Association at Ordinal Level
                        WORK:  Quiz 5
                                       Assignment #6:  Chapter 13:  Problems  13.1, 13.5, 13.7, 13.11
                                                                Chapter 14:  Problems  14.1, 14.5, 14,7, 14,11
04/30/11:  Chapter 15:  Association at Interval-Ratio Level
                 Chapter 16:  Bivariate Tables
                 Chapter 17:  Regressions/Correlations
                       WORK:  Quiz 6  and Finalization of project reports
                                      Assignment #7:  Chapter 15:  15.9
                                                               Chapter 16:  16.1
                                                               Chapter 17:  17.1
05/07/11:  Core Assessment Oral and Written Reports
                 Quiz 7 and Final Exam

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 ( or Park University 2010-2011 Undergraduate Catalog Page 92

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: .


CompetencyExceeds Expectation (3)Meets Expectation (2)Does Not Meet Expectation (1)No Evidence (0)
Analysis & Evaluation                                                                                                                                                                                                                                      
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  
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                                                                                                                                                                                                                                             
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.  


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Last Updated:3/6/2011 3:50:17 PM