Final exams and final grades for fall 2002
(by last TWO digits of student ID number)
id, then final exam grade, then course grade
019 83 A-
035 82 B+
105 96 A+
114 76 B+
184 80 B+
205 95 A+
235 84 A-
277 72 B-
423 88 A
465 90 A-
516 85 A
551 71 B-
686 63 B
821 95 A
853 85 B+
887 86 A-
910 94 A
985 86 A-
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University of Oregon, Fall 2002
Psychology 412: APPLIED DATA ANALYSIS
Straub 180, Tuesdays and Thursdays 10:00 - 11:20 am
with lab section Fridays 9:00 - 9:50 am
For graduate students, this course is Psychology 512
Professor: Gerard Saucier, Ph.D.
Office: 312 Straub
E-mail: gsaucier@oregon.uoregon.edu Phone: 346-4927
Office Hours: Tuesdays 1-2 pm, Thursdays 2-3 pm, or flexibly by appointment
Teaching Assistant: Laura K. Jones, 339 Straub, 346-1997, ljones@darkwing Office Hours: TBA.
Texts: Shannon, D. M., & Davenport, M. A. (2001). Using SPSS to solve statistical problems.
Upper Saddle River, NJ: Merrill Prentice-Hall plus extra readings provided by the
instructor
Web page: http://darkwing.uoregon.edu/~gsaucier/ps412_02.htm
Course prerequisites: Psychology 302 and 303, or equivalent, or instructor's permission; access
to e-mail and an internet browser also will be very helpful
Course Objectives (or, what's the purpose of this course?)
Welcome to Psychology 412. This is a course about statistical analyses, which function to help scientific investigators discern patterns in phenomena, and determine the relative generalizability of these patterns This is an intermediate course in statistics for psychology, designed for those who may be in the near future beginning to conduct research and carry out statistical analyses. It focuses on analysis of variance and regression techniques. The course objectives are the following:
1. Developing your ability to understand and explain to others the statistical analyses in reports of social and behavioral science research.
2. Developing your ability to identify the appropriate statistical procedure for many basic research situations and to carry out the necessary computations, with a widely-used statistical program.
3. Generally furthering development of your quantitative and analytic thinking skills.
Our focus will tend to be conceptual rather than mathematical, applied rather than theoretical. During the course we will make abundant use of computer software, although you will also be asked to carry out hand computations illustrating key statistical principles.
What methods are used for learning? Reading assigned material, completing the assigned problem sets (homework practice exercises), and turning them in on time. Attending the class sessions, listening closely, asking questions, having done the reading first. And finally, studying for, taking, and reviewing answers for quizzes.
The class format is a mixture of prepared presentations (i.e., lecture) with response to questions and hands-on work with computer. There will also be some in-class exercises, focusing primarily on how the concepts learned in the class can be applied.
Summary of Basis for Evaluation
Your final course grade is based on the following components:
30% Score on the problem sets (homework assignments)
Note: as a prerequisite to pass the course, it is necessary to complete and turn in all
problem sets by the time of the final exam
5% Satisfactory compilation of a stats reference notebook for yourself to use after course
30% Average score on the quizzes
25% Score on the cumulative final examination
7% "Sufficient participation" (defined below) on in-class practice-tests
3% Contributing your share of the educational-purposes-only data set we will use
This final percentage is then converted into a grade. A range is 90% to 100%, B range is 80% to 90%, C range 70% to 80%, D range 60% to 70%, with '+' and '-' being assigned if the percentage is within the top or bottom 1/3, respectively, of each of these ranges. F is ó 59.99%.
Each graduate student will be required to carry out an additional project on a topic relevant to his/her field and/or interests (please consult with the instructor during the first half of the term).
How Your Learning Progress Is Evaluated in Psychology 412
In order to give ongoing performance feedback, and help students keep focus on the important subject matter of this course (a prerequisite to upper division courses in psychology), the course is designed with several quizzes, as well as many opportunities to take practice-tests for the quizzes in order to help you find out what you might especially need to work on for the quizzes, and generally learn more about.
There will be three quizzes. Quizzes consists of "problem" items, as well as multiple-choice and at least sometimes mini-essay items. 45 minutes starting near the beginning of a class session will be allotted to each quiz, and there will be a regular class session (i.e. for about 25 minutes) consuming additional class time after each quiz. If you have to miss a quiz, consult with the instructor about make-up opportunities during the final exam period.
On seven Tuesdays of the term you'll have the opportunity to take a practice-test (about 5minutes allotted). These are based on the readings assigned for that Tuesday, and are very brief (typically only one or two items), designed to give you more feedback about how well you are learning specific aspects of course content, and as a springboard into talking about the content in the readings. They are pedagogical exercises, rehearsals, rather than real tests. As such, they are graded only on a "sufficient participation" basis. As long as you get at least 50% credit on over 50% of the practice-tests (4 of the 7) you get full credit for this part of the course (getting 50% credit on 3 of them gets 3/4 credit overall, 2 of them gets 1/2 credit, 1 of them gets 1/4 credit). We go over practice-test answers in class immediately after taking them.
The cumulative final examination will be designed like a quiz, generally. A study guide for the final will be provided during the last week of class (8-10 days before the final). This exam is cumulative so as to encourage you to review key points from the course and thus enhance what you take away from the course. Practice-tests, quizzes, and the final exam are all open-book.
Friday sessions (or "lab sessions") will consist of a combination of (a) review of material, (b)an extra chance to have your questions answered, and (c) training on use of computers and statistical software, which are incorporated in some of the problem-sets assignments.
Once each two weeks problem sets are handed out, and the due date is one week later. Those turned in late get, at best, half credit. Four problem sets count toward your final grade; if you turn in all five, the highest four scores count. You are required to complete all problem sets assignments in order to pass the course. Problem sets are evaluated on a 10-point scale. Policies on working with other students on the problem sets will be set by the TA (Laura K. Jones). If you have difficulties with the problem sets, please consult the TA or the instructor.
In general, you are encouraged to discuss problem sets with other students and with the teaching assistant, and to compare your work with others before turning it in. Problem sets help you learn skills by practicing. Talking over the problems and reworking them when you discover that others got different answers promotes deeper understanding of concepts and gives you more practice in applying skills. However, each student must submit separate problem sets, and you must show your work (no photocopies or word-for-word copying). And all problem sets must be turned in by the start of the final exam to pass the course.
You are asked to compile a statistics reference notebook for yourself during the course, that you can use as a resource after you have completed the course. The minimum requirements for this reference notebook are set by the TA. This notebook must be turned in by the last Friday lab session (Dec. 6), unless arranged otherwise by the TA, so that it can be returned to you by the final.
You are strongly encouraged to bring a hand calculator to class, as you may find this more convenient than the computer for some simple work. A simple calculator that adds, subtracts, divides, multiplies, and takes square roots is all that you'll need.
In this course we will be using SPSS for Windows version 10 (or later) software. This software is installed on the machines in 180 Straub (open 8 am - 9 pm Monday through Thursday, 8 am - 5 pm Fridays). It is also available in the Social Science Instructional Laboratory (Grayson Hall), which is also open at night and on weekends. There has been in the past a $10 fee per term for use of SPSS at SSIL. Please contact me if you are interested in using SSIL, so I can track how much we need and use this facility. If desired, you might purchase your own copy of SPSS 10 from the software section of the Bookstore (approx. $165 if you are a full-time student; correct version would be SPSS Graduate Pack for Windows 10.0 Advanced Version with Base, Professional, and Advanced modules).
One may submit written challenges to a quiz grade immediately after a quiz is administered. Grades will be adjusted only if the challenge is successful and only for the individual challenging.
The instructor takes academic integrity seriously. Insuring the "validity" of grades requires seeing that they reflect honest work and learning rather than cheating. Cheating is defined as providing or accepting information on an exam, plagiarism or copying anyone's written work. Students caught cheating will be given an "F" for the course, and UO's student conduct coordinator will be informed.
PSYCHOLOGY 412/512 SCHEDULE: Tuesdays and Thursdays
(Note: S & D refers to the Shannon and Davenport text)
Oct. 1 Syllabus; overview of the course; preparatory activities, some review
Reading: S & D chapters 5-6
Oct. 3 Frequency distributions, central tendency (mean), variability (variance,
standard deviation), normal curve (and skew)
Reading: S & D chapter 11 plus additional reading
Oct. 8*, 10 Introduction to hypothesis testing; Type I and II error; power analysis
Reading: S & D chapters 12-13
Oct. 15* Measures of association; chi-square analysis
Note: Oct. 17 is an extra lab meeting date
Reading: S & D chapter 14 plus additional reading
Oct. 22*, 24 Measures of association; correlation
Oct. 25 Quiz 1
Reading: S & D chapter 16 and additional reading
Oct. 29* Comparing variances; one-way analysis of variance
Reading: S & D chapter 15
Oct. 31 The t-test (and why we will rarely use it); multiple comparisons in ANOVA
Reading: S & D chapter 17 and additional reading
Nov. 5*, 7 Factorial analysis of variance
Reading: S & D chapter 19 and additional reading
Nov. 12* Repeated measures ANOVA
Reading: S & D chapter 21
Nov. 14 Introduction to regression model; how regression relates to ANOVA;
bivariate regression (this content will be covered on Quiz 3, not Quiz 2)
Nov. 19 Quiz 2
Reading: to be announced
Nov. 21 Multiple correlation; partial and semipartial correlation
Reading: S & D chapters 22-23 and additional reading
Nov. 26*, Dec. 3 Multiple regression
Dec. 5 Quiz 3; integration of course material for comprehensive final
Dec. 13 (Friday) 8 a.m. Final exam * indicates a practice test is given that day