CRN 14351, 4 credits

Syllabus: Applied Data Analysis

Psy 412/512,  Fall 2003,  TuTh, 10:00-11:20 A.M., Lab Fr 9:00-9:50, 180 Straub

 Professor Office E-mail Phone Office Hours Dr. Holly Arrow 357 Straub harrow@darkwing. uoregon.edu 346-1996 Tues 11:30-12:30 Wed 10:30-11:30 Chuck Tate 356 Straub 346-1060 Mon 2-4 PM

Class Blackboard site: http://blackboard.uoregon.edu/ _______________________________________________________________________

Course Goals:

1. Improve your ability to identify patterns in data, relate these patterns to substantive issues about the topic under investigation, and communicate your results and your interpretation in writing.  2. Sharpen your quantitative and analytical reasoning skills.   By the end of the course you should be able to

• generate a plan for analyzing a data set, choosing methods appropriate to both your research questions and the structure of the data
• execute your data analysis plan using SPSS for Windows
• understand and summarize the results in your printout
• interpret the meaning of the results in relation to your research questions and communicate your insights in writing

Course Description:  This course focuses on the concepts and methods of descriptive and inferential statistics at an intermediate level.  Topics include ANOVA & ANCOVA, linear and multiple regression, nonparametric methods for ordinal data, and categorical data analysis, including chi-square, log-linear models, and logistic regression.  By the end of the course, you will have some understanding of each of these methods.  Your understanding will vary across topics, and that is fine.  Statistical training is a lifelong process.  I will treat you as colleagues in training, and see my role as guide, coach, and fellow traveler.

Writing Skills:  Homework includes writing up results and interpreting them for the reader.  Strunk & White’s The Elements of Style can help you write concise, precise sentences.  Review the eight elementary rules of usage and the ten elementary principles of composition at http://www.columbia.edu/acis/bartleby/strunk/index.html

Learning Disabilities: Contact me right away (first week of class) if you have been  diagnosed with a learning disability (confirmed by the Academic Learning Center) or have some other special needs that may require adjustments.

Class Requirements and Activities:

1. Required Readings.  Everitt, Brian S. (2001).  Statistics for Psychologists: An Intermediate Course & Gardner, Robert C. (2001).  Psychological Statistics Using SPSS for Windows.  See last page for readings assignments.

2. Participation. Attendance and participation during class and lab are required.  Bring a calculator to class, since this is more convenient than the computer for some calculations.  A simple calculator is fine; if you have a fancier one, make sure you know how to use it J

3. Written responses to readings.  Every Tuesday, you will prepare a short *typed* response to the assigned Everitt chapter.  Bring two copies, one to hand in, one to refer to during class.  Your response will have two parts. First, identify what you see as the three most important points in the chapter, and write a sentence explaining each point to the best of your ability.  Second, identify three issues or points that you find confusing or hard to understand.  Write a sentence for each, explaining what you find problematic. I will call upon students to share and explain one or more of their main points in class.  Late responses earn half credit.

4. Homework.  Homework will consist of conceptual questions and problem sets.  To earn full credit, show and explain all work, and annotate your computer printouts.  Summarize the output of your analyses in a *typed*  “results” paragraph and discuss what they mean in a *typed*  “discussion” paragraph, following APA guidelines as given in the 5th edition of the Publication Manual.  This will develop your skill in presenting and explaining analyses.  Crunching numbers is of limited use if you can’t present and interpret your results clearly. Late homework earns half credit; quarter credit if more than one week overdue,*unless other arrangements are made in advance with Chuck.  Missed points on homework may be challenged *only* for homework turned in on time. Challenges due within a week of when corrected homework is returned.

5. Quizzes.   We will have short quizzes every Thursday on the chapter for that week.  Quizzes are a learning tool that provide you with feedback about what you do and do not yet understand.  There will also be occasional “pop” quizzes about material covered in previous weeks.  Pop quizzes will focus on material that people did poorly on in regular quizzes, so study up on any questions you missed!  Class will determine grading scheme.

6. Final. The take-home final will include conceptual questions, “generate a plan” questions that ask you how you would analyze a data set, plus the actual statistical analysis and interpretation of one or more data sets (following format established by the homework).  Due Wed Dec. 10th, by 10 AM.  Turn in at my office, 357 Straub.
Class point breakdown for grades (300 points possible)

Attendance & participation                  20 pts  (full participation = full points)

Responses to readings:                         40 pts  (8 satisfactory responses, turned in on time)

Homework sets:                                   80 pts (best 8 out of 9, all 9 must be turned in)

Quizzes:                                               60 pts (7 chapter quizzes, 3 “pop” quizzes)

Final exam:                                          100 pts

 Course grades based on percentage of points earned A+ 97-100 C 73-76.9 A 93-96.9 C- 70-72.9 A- 90-92.9 D+ 67-69.9 B+ 87-89.9 D 63-66.9 B 83-86.9 D- 60-62.9 B- 80-82.9 N < 70 C+ 77-79.9 P 70

Cheating, if detected, will earn a failing grade in the course. Cheating =  turning in the work of others as your own, copying other people’s quiz answers, or copying from someone else’s final exam.  For the final, providing or asking for help from other students in the class = cheating.  See below for legitimate input on the final.

What is NOT cheating, but helpful collaborative learning?  Getting or providing help on the homework.  Meeting to compare notes on homework (in person or on Blackboard) can help everyone do well.  However, don’t just copy what someone else has done—complete the homework yourself.  For the final: It’s fine to have someone outside the class  read a draft of your final to see if it is clearly written. When writing academic papers, scholars should get feedback from colleagues before submitting the final product to a journal J

Class Etiquette & Norms

Please come to class and lab on time, and stay for the whole class or lab

If you must miss a class or leave early, let me or Chuck know

Turn your cell phone OFF during class unless you are a doctor on call

Ask questions and speak up during class

Stop by and see me and Chuck during office hours

Homework Assignments:

Homework #1:  Do problems 2.2 & 2.5 in Everitt (pp. 59, 62).  For each problem, type up a results paragraph (describing what you did) and a discussion paragraph (explaining what it means for the research topic).  Follow APA Publication Manual, 5th edition, for the format of reporting statistical tests.   Also include your graphics, of course!

Other Homework assignments will be given separately.

 SCHEDULE Reading in Everitt, Statistics for Psychologists          Read by TUESDAY Reading in Gardner, Psychological Statistics Using SPSS            Review by THURSDAY Assignments & Activities:  Responses, Homework sets, quizzes Week 1 Sept 30, Oct 2,3 Chs 1 & 2 Intro & Graphical Methods Ch. 1 & 2 (skim as a refresher for basics, t-test) Tues:  Diagnostic Test Thursday: Response to Ch. 2 Week 2 Oct 7, 9, 10 Ch 3 ANOVA One-way Ch. 3 Single Factor ANOVA Tues: Homework #1, Response to Ch. 3   Thurs: Quiz #1 Week 3        Oct 14, 16, 17 Ch 4 ANOVA Factorial Ch 4 Randomized Factorial Tues: Homework #2, Response to Ch. 4   Thurs: Quiz #2 Week 4 Oct 21, 23, 24 Ch 5 Repeated Measures ANOVA Chs 5 & 6    Repeated & Split-Plot GLM Tues: Homework #3, Response to Ch. 5   Thurs: Quiz #3 Week 5 Oct 28, 30, 31 Ch 6 Regression Chs  9 Multiple Regression Tues: Homework #4, Response to Ch. 6   Thurs: Quiz #4 Week 6 Nov 4, 6, 7 Ch 7 Longitudinal Data NA Tues: Homework #5, Response to Ch. 7   Thurs: Quiz #5 Week 7 Nov 11, 13, 14 Ch 8  Distribution-Free Methods NA Tues: Homework #6, Response to Ch. 8   Thurs: Quiz #6 Week 8 Nov 18, 20, 21 Ch 9  Categorical Data I: Chi-Square Ch 7 Chi-Square Tues: Homework #7, Response to Ch. 9   Thurs: Quiz #7 Week 9 Nov 25 only Ch 10  Categorical Data II: Log-linear, Logistic regression None Tues: Homework #8, Response to Ch. 10 Week 10      Dec 2, 4, 5 Ch 10 cont. & Review None Fri Dec 5, by 3 PM: Homework #9 Finals Week:   Take Home Final Exam:  Due by 10 AM, Wed Dec 10. Bring to 357 Straub.