SO 307 Statistics for Social Sci.
U1QQ 2012 HI
Hulphers, Eric A.
PhD Health Promotion & EducationMS Human Resource Management
bld 383 room 113
T & Th 12;pm to 4:pm
04 June – 29 July 2012
4:30 - 7:15 PM
An introductory social science class (i.e., SO141, PS101, CJ100, or SW205) and MA131 or equivalent
Additional Resources: Students will need to have access to a computer, and if possible, a laptop brought to class.
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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
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 RubricClass 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.
Healey Ch. 1 – Intro to Course;
How to Lie with Statistics
Healey Ch. 2 – Descriptive Stats;
Healey Ch. 3 – Measures of Central Tendency;
Healey Ch. 4 – Measures of Dispersion
Healey 5 – Normal Curve;
Healey 6 – Intro to Inferential Stats
Healey 7 – Estimation Procedures;
Healey 8 –Hypothesis Testing I
Healey 9 – Hypothesis Testing II;
Healey 10 –Hypothesis Testing III
Healey 11 – Hypothesis Testing IV;
Healey 12 – Bivariate Association
Healey 13 – Nominal Level Measurements
Healey 14 – Ordinal Level Measurements;
Healey 15 – Interval-Ratio Level Measurements
Healey 16 – Elaborating Bivariate Tables;
Healey 17 – Partial Correlation and Multiple Regression
Final Data Analysis Report (Core Assessment) & Quiz 7
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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.
Park University 2011-2012 Undergraduate Catalog Page 96
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Last Updated:4/16/2012 10:48:17 AM