PSYCHOLOGY 302
STATISTICAL METHODS IN
PSYCHOLOGY - SPRING 2003
Straub 146 MW 12:00 -
1:20
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Professor: |
Teaching Assistant: |
Teaching Assistant: |
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Dr. Lou Moses |
Jonathan Cook |
George Slavich |
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Phone:
346-4918 |
346-4963 |
346-1984 |
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Office:
397 Straub |
329 Straub |
393 Straub |
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Office Hours:
T 10-11; W 2-3 |
T 1:30-3:00 |
Th 4-5 |
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E-mail: moses@darkwing |
jcook4@darkwing |
gslavich@darkwing |
Course Description: This class is the first in a sequence of two
methodology courses for students intending to major in psychology. It provides
an introduction to basic statistical concepts, methods, and applications. The aim of the course is to encourage the
development of practical skills in the analysis and interpretation of real
psychological data, and to help students become educated consumers of the
research literature in psychology and related fields. To that end, our focus
will tend to be conceptual rather than mathematical, applied rather than
theoretical (e.g., it will be more important to understand why a particular
statistical technique is appropriate, and how to make sense of the results
obtained from its use, than to understand the full mathematical underpinnings
of the statistic). During the course we
will make frequent use of the computer to analyze data, although you will also
be asked to carry out hand computations illustrating key statistical
principles. You don't need to be an accomplished mathematician to do well in
this course. The ability to reason in a
logical manner is more important to successful understanding of psychological
statistics than the ability to manipulate complex equations. The course does
involve numbers -- there's no escaping that -- but if you have basic arithmetic
and algebra skills, the mathematical component of the course will be
straightforward.
Course
Prerequisites: Mathematics 111 or
equivalent.
Required Textbooks:
Aron, A. & Aron E.N.
(2002). Statistics for the Behavioral and Social Sciences: A Brief
Course (2nd. Ed). Upper Saddle River, NJ: Prentice Hall.
Renner, C. (2002). Study
Guide and Computer Workbook. Upper Saddle River, NJ: Prentice Hall.
Lectures and Laboratories: Attached is a list of lecture topics and reading
assignments. Please read the relevant
section of the text before the lecture to which it corresponds. Note
also that lecture notes will be available on the Blackboard web site (see
below) prior to each class. To avoid
copying down class overheads, please bring these notes to class. In addition to attending lectures, you must
also enroll in and attend one of the 3 weekly statistical laboratories run by
the class TAs: Mon 2-3:20 (George); Tues 8:30-9:50 (Jonathan); Tues 12-1:20
(Jonathan). The labs will be held in 180
Straub, the Psychology Department’s computer lab (open 8am-9pm Monday through
Thursday, and 8-5 Friday). The labs will
provide an opportunity to gain hands-on computing experience relevant to
concepts discussed in lectures. The statistical software for this course is
SPSS for Windows Version 11.5. It is
installed on the computers in 180 Straub.
The labs will also involve discussion of the weekly problem sets, as
well as allowing you the chance to raise any questions you have concerning
lectures or the textbook. Labs begin in Week 1 with an introduction to the SPSS
computer package.
Exams: There will be two
midterms and a final exam. Make-up exams will only be given in extreme
circumstances (e.g., serious illness or injury) and there will be no early
exams. All exams will be cumulative,
with an emphasis on more recent material.
Exams will be closed book. Questions will mostly be conceptual but some
will involve calculation. However, since
comprehension rather than memorization is the goal, we will provide a list of
mathematical formulas; your job will be to know what formula is relevant to a
particular problem and how to use it correctly.
It will be helpful to have a calculator for the exams but to receive credit
for calculation problems you will need to show each step of your calculations;
do not rely on advanced calculators that directly compute complex
formulas.
Problem Sets:
To
understand is to do: Just like
practicing piano or tennis, you need to exercise your statistical muscles. To help you with this, take home problem sets
will be assigned each week. Assignments
will normally be due in class on the Monday after they are handed out. Late problem sets will not be graded
unless prior arrangements have been made. The problem sets will be graded
on a 10 point scale (0-10). Collaborative learning is encouraged: If you want
to discuss the problems with other students, feel free to do so. However, the
answers you turn in should be written independently. If you have difficulties with the problems,
please consult with the TAs or with me.
Grading: The problem sets will
count for 30% of your grade, the midterms for 20% each, and the final for 30%.
Blackboard: The course web site can be accessed through the
Blackboard course information system. On the web site, you will find general
announcements for the class, lecture notes, problem sets and solutions, links
to relevant web sites, and more. You will need an account on the Blackboard
system; students enrolled in the course will receive email before the first
week of the term with their account name and initial password. To visit the
course site, go to http://blackboard.uoregon.edu,
login, and then select "Statistical Meth Psych" from the list of
blackboard course sites in which you are enrolled. If you need help logging in
or using Blackboard, see http://blackboard.uoregon.edu/local/usingbb/.
Also you can get help by going to the library Information Technology Center (ITC)
and/or see http://libweb.uoregon.edu/kitc/faq/blackboard.html#help.
OUTLINE
OF LECTURE TOPICS
|
Date |
Topic |
Reading |
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March 31 |
Introduction |
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April 2-9 |
Exploratory Data
Analysis |
Appendix 1 in Renner |
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April 14 |
The Normal
Distribution |
Ch 4 |
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April 16-21 |
Sampling Distributions |
Ch 5 |
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April 23 |
MIDTERM 1 |
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April 28-30 |
Hypothesis Testing and
Estimation |
Ch 6 & 7 |
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May 5 |
One Sample T-Test |
Ch 8 |
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May 7 |
Two Sample T-Tests |
Ch 9 |
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May 12 |
MIDTERM 2 |
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May 14-19 |
Analysis of Variance |
Ch 10 |
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May 21 |
Correlation |
Ch 3 |
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May 26 |
Memorial Day |
|
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May 28 |
Regression |
Ch 3 |
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June 2 |
Chi-Square |
Ch 11 |
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June 4 |
Future Directions |
Ch 12 |
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June 13 |
FINAL EXAM (10:15 -
12:15) |
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