Syllabus Entrance
Printer Friendly
Email Syllabus

SO 307 Statistics for Social Sci.
Rahnama, Cyrus

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.


SO 307 Statistics for Social Science


F1B 2012 BL


Rahnama, Cyrus


Adjunct Faculty


Master of Science in Mathematics
M.S. in Electrical Engineering
MBA in Business Administration

Office Location

Bldg 616, Rm 10, Ft. Bliss

Office Hours

Contact me by email or phone if you have additional concerns/ questions outside the classroom or we may discuss before or after class

Daytime Phone


Other Phone



Semester Dates

August 20, 2012 to October 14, 2012

Class Days


Class Time

8 AM to 1 PM


An introductory social science class (i.e., SO141, PS101, CJ100, or SW205) and MA120,  MA131 or equivalent.

Credit Hours



Required Text:  Healey, J.F. (2012). Statistics: A tool for social research (9th ed.).
Stamford, CN: CENAGE Learning-Wadsworth.
Huff, D. (1954/1993). How to lie with statistics (1993 Reissued ed.). New
York, NY: W.W. Norton & Co.
 - Manual of the American Pyschological Association - 6th edition
 - APA's website
 Please bring your textbook and scientific calculator to the class room during all class sessions.

Textbooks can be purchased through the MBS bookstore

Textbooks can be purchased through the Parkville Bookstore

Additional Resources:


In response to the needs of our students, Park University (FTBL) and El Paso Community College (EPCC) have partnered to provide tutoring services in Mathematics and Statistics. I have been informed that the services will be free of charge to all students. We have chosen the Valle Verde Campus located at 919 Hunter (Bldg A) due to their central location to Fort Bliss. EPCC Tutoring Services hours of operations are as follows:

Mon-Thur: 8am-7pm

Fri: 8am-3pm

Sat: 9am-2pm

Please use this valuable service.


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 or call 800-927-3024
Resources for Current Students - A great place to look for all kinds of information

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: MA120,  MA131 and an introductory social science class (i.e., SO141, PS101, CJ100 or SW 205)

Educational Philosophy:

My educational philosophy is based on engaging the student in active learning through classroom discussion and participation through the use of a variety of methods in learning: Lectures, readings, tests, group work class discussion, writing, and the use of reference systems are significant components of this learning process.
Thus, students are expected to use all course related sources in order to meet the course’s overall objectives:
Establishing an open environment for intellectual stimulation via lecture, group discussion and audio visual aid.
Provide access to academic excellence with the latest and most current research and discoveries through assigned group projects and Internet exploration.
Finally, prepare the student for critical thinking and effective communication via writing assignments and class presentations/assignments.





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:

  ggg   Regular Assignments: These will consist of unit problem sets and short answer conceptual and application questions. Every week, I will designate a homework assignment. You will be expected to complete your assignment in class, hand it in at the beginning of the next class session, or in the online dropbox as designated. I recommend that you type your homework assignments. There are a total of 6 homework assignments. In grading regular assignments, I will mainly be looking for evidence that you read the readings. I will not accept any late assignments.
   Discussion and Participation: Attendance and participation are vital to the successful completion of this course because quizzes will be based on lecture materials as well as assigned textbook readings and anything else covered in class. It is your responsibility to sign the attendance sheet as well as obtain any information missed (due to your absence) from your fellow classmates. Includes class assignments (cannot be made up). 

   Unit Quizzes: Four short quizzes. Cannot be made up. 

   Final Exam: The Final Exam will consist of multiple-choice, true-false, fill-in-the-blank, and short answer questions. The exam may include information from class lectures, the textbooks, videos, and the assigned readings.





Total Points


Unit Quizzes (Week 2-6)

20 x 4


8 %

Homework Assignments (Week 1-6)

50 x 6


30 %

Class Attendance/ Participation (Weeks 1-8)

10 x 8


8 %

Data Analysis Project (Week 8)



20 %

Midterm (Week 4)



14 %

Final Exam (Week 8)



20 %



           1000    (100%)  

Grading Scale:
Based on accumulated points; NOT based on +/- scale

















Below 300

Below 59.9%

See attached file rubric for additional details.

Late Submission of Course Materials:

No late course materials will be accepted after the last class meeting date.
An equivalent of 0.5 points will be deducted per day for homework assignments that are late. There are no make ups for missing quizzes. Mid-term exam can be taken after the exam date only with extenuating circumstances and proper documentation and by contacting the instructor

Classroom Rules of Conduct:

  • Strive to be professional and respectful to your classmates.
  • Place cellular phones in silent mode, so the class is not disturbed
  • Give the person talking in class, regarding the topic of the day, your undivided attention
  • No eating in the class room per the university rules

Course Topic/Dates/Assignments:





Activities & Due assignments


August 25th


Introduction to Statistical terms and Levels of Measurement

CH 2

Descriptive Statistics: Percentages & Frequencies

Review of Course Syllabus

Intro to Statistics

Homework 1: Due on Saturday, September 1st at 8:00 AM


September 1st

CH 3: Measures of Central Tendency

CH 4: Measure of Dispersion

Quiz 1

Homework 2: Due on Saturday, September 8th at 8:00 AM


September 8th

CH 5: The Normal Curve (z-scores & Probability)

Quiz 2

Homework 3: Due on Saturday, September 15th at 8:00 AM


September 15th

CH 6: Sampling

CH 7: Estimation Procedures

Mid-Term Exam Review

Homework 4: Due on Saturday, September 22nd at 8:00 AM


September 22nd

Mid-Term Exam

CH 8: One-way Samples, T-test

CH 9: Two way Samples, T-test

Mid-Term Exam

Homework 5: Due on Saturday, September 29nd at 8:00 AM


September 29th

CH 11: Analysis of Variance

Bivariate Measures of Association

CH 12: Nominal level

CH. 13: Ordinal level

CH 14: Interval-Ratio Level

Quiz 3

Homework 6: Due on Saturday, October 6nd at 8:00 AM


October 6th

CH 15: Elaborating Bivariate Tables

CH 16: Partial Correlation, Multiple Regression, Correlation.

Final Exam Review

Quiz 4


October 13th

Final Exam

Final Exam

Data Analysis Project due on Saturday, October 13 at *:00 AM (MST).

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 2011-2012 Undergraduate Catalog Page 95-96

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.

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: .

Additional Information:

Students are encouraged to use ecompanion to download (DocSharing tab) the information from the instructor.

Student may also use ecompanion to monitor their status (grades and assignments)


Please turn laptops off during class, unless otherwise directed by the instructor.

Accessing ecompanion

Accessing ecompanion

Accessing ecompanion


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.  


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

Last Updated:8/17/2012 10:47:44 PM