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SO 307 Statistics for Social Sci.
Hulphers, Eric A.


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

SO 307 Statistics for Social Sci.

Semester

U1QQ 2012 HI

Faculty

Hulphers, Eric A.

Title

Senior Professor

Degrees/Certificates

PhD Health Promotion & Education
MS Human Resource Management

Office Location

bld 383 room 113

Office Hours

T & Th 12;pm to 4:pm

Daytime Phone

801-726-0670

E-Mail

eric.hulphers@park.edu

eric.hulphers@erau.edu

Semester Dates

04 June – 29 July 2012

Class Days

--T-R--

Class Time

4:30 - 7:15 PM

Prerequisites

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

Credit Hours

3


Textbook:
 

Healey, J. (2012). Statistics: A Tool for Social Research, 9th ed. Thomson Learning-Wadsworth.
(Bundled by MBS with SPSS  Student Edition & SPSS Guide.)

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

ISBN: 9781111186364 as bundle

Additional Resources:
Students will need to have access to a computer, and if possible, a laptop brought to class.

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/.


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:

Learning is an interaction between student, instructor, and other students.  To facilitate this, class time is used to explore the concepts and enhance the learning processes. Questioning, asking, discussing, and critical thinking are just parts of the learning process that will occur. 

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:
 

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.

Mid term exam ( 90 points total = 14%)

Final Exam (1000 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

Late Submission of Course Materials:
 

Students may make up a missed test or quiz, but the student will lose some or all of the total possible points on if the student has made previous arrangements.  Any homework assignments that are turned in late, no credit will be given.  Any absences that occur the student must have 3rd party documentation of the reason, i.e. TDY order, leave orders, medical, etc. No makeup of materials will be allowed without said documentation.

Classroom Rules of Conduct:
 

The use of cell phones or pagers in class is not permitted except for those who are on call for work purposes.  All cell phones and pagers are to be either turned off or set to vibrate.  No texting during class time. 

Course Topic/Dates/Assignments:
 

Week

Chapter/Topic

Assignments Due

1:

Healey Ch. 1 – Intro to Course;
How to Lie with Statistics
Healey Ch. 2 – Descriptive Stats;

Pre-Quiz           

2:


Healey Ch. 3 – Measures of Central Tendency;

Healey Ch. 4 – Measures of Dispersion

Assignment 1

3:

Healey 5 – Normal Curve;

Healey 6 – Intro to Inferential Stats

Assignment 2

4:

Healey 7 – Estimation Procedures;
Healey 8 –Hypothesis Testing I

Assignment 3

5:

Healey 9 – Hypothesis Testing II;

Healey 10 –Hypothesis Testing III

Assignment 4

6:

Healey 11 – Hypothesis Testing IV;

Healey 12 – Bivariate Association

Healey 13 – Nominal Level Measurements

Assignment 5    

7:

Healey 14 – Ordinal Level Measurements;

Healey 15 – Interval-Ratio Level Measurements

Assignment 6

8:

Healey 16 – Elaborating Bivariate Tables;

Healey 17 – Partial Correlation and Multiple Regression

Final Exam

Final Data Analysis Report (Core Assessment) & Quiz 7

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 93

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 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 2011-2012 Undergraduate Catalog Page 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)
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.  

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Last Updated:4/16/2012 10:48:17 AM