Syllabus and Course
Contract for
PSY 138: Reasoning in Psychology Using
Statistics
Section 01: MW 11-11:50
Fall 2007
Contact Information
| Instructor: |
W. Joel Schneider |
| Office: |
De Garmo 447 |
| Phone: |
438-8410 |
| e-mail: |
wjschne@ilstu.edu |
| office
hours: |
Tuesdays 2-3pm
Wednesdays 10-11am
and by appointment |
|
Graduate Assistant:
|
Chris Sorric
|
|
e-mail:
|
chrissorric@hotmail.com
|
| Sections |
MW 2-2:50 DeGarmo 13
MW 3-3:50 DeGarmo 13 |
|
office hours and location:
|
TBA
|
|
Graduate Assistant:
|
Ying Ong
|
|
e-mail:
|
yyong@ilstu.edu
|
| Section |
MW 12-12:50
DeGarmo 13
MW 1- 1:50 DeGarmo 13 |
|
office hours and location:
|
TBA
|
Description
Students develop skills both in statistical reasoning and statistical
method
by actively engaging in the practice of statistics as science. Students
will study important current, psychological issues whose understanding
requires a fundamental knowledge of statistical concepts, in
particular,
hypothesis testing and regression. Controversial topics will be chosen
that are currently in the news and likely to remain so. Such
psychological
controversies are regularly found in journals and magazines such as American
Psychologist and Current Directions in Psychological Science.
Reasoning in Psychology Using Statistics uses a
classroom/laboratory
approach for analysis of data, for hands-on production of data, and for
simulation-based learning. According to Cobb (1993, p.4), "the lab
approach
accords with the movement of statistics back towards its roots in
science,
and with research in education that demonstrates the importance of
active
learning." Additionally, the classroom/lab setting allows students to
access
the vast array of data available through the Internet.
Reasoning in Psychology Using Statistics follows the
guidelines
developed by the American Statistical Association (ASA) and the
Mathematical
Association of America (MAA) which suggest that teachers should:
- Motivate students by showing them statistics at work in real
applications,
problems, cases, and projects.
- Use real data and statistical computing (SPSS).
- Foster active learning
Textbooks (Very Optional)
Almost any introductory social science statistics textbook will be
helpful. Here is one that I used to require:
Social
Statistics for a Diverse Society (3th edition) by Chava
Frankfort-Nachmias & Anna Leon-Guerrero (Pine Forge Press, 2002).
The reason I no longer require a textbook is that there are so many
free statistics resources on the
web. A quick search on the search engine of your choice will probably
bring new ones every day.
Here is a free
statistics textbook.
Here is another.
If you learn best by listening, there are a number of podcasted
introductory statistics courses. You don't need an iPod to listen to
them. You can listen on any computer with speakers. Here is one from my
alma mater, UC
Berkeley.
MIT has a large number of courses with free content on all kinds of
topics. Here are downloadable
slides on introductory statistics.
Software
SPSS (Release 14.0) SPSS,
Inc. - this software is available on the classroom
computers and on most other campus lab computers. You do NOT have to
purchase
it for the class, however if you want a copy for your home computer,
student
versions are available at the student bookstores.
I will also use Microsoft Word and Microsoft Excel often and will
sometimes give you Excel tools for statistics. If you don't have
Microsoft Office, OpenOffice.org
offers a FREE, high-quality office suite that is compatible
with Microsoft Office. Althought OpenOffice uses a different format by
default, you can save documents and spreadsheets
in OpenOffice in the same format that Microsoft Office users use. A lot
of
free software is not very good. OpenOffice is a major exception. You
can also try Google Docs and Spreadsheets for free.
Required Materials
"Clicker" or RF Response Card (How to
get one). I explain how I use these in class in the "Attendence"
section below.
Calculator: I haven't used a hand calculator in years (I use
Excel for
everything.). However, most students will probably want to use a
calculator for the course. Any reasonable calculator with a memory
button will work. You are not permitted to use your cell phone's
calculator on exams.
Attendence
You are expected to attend every lecture
and participate through discussion and classwork.
Lecture and lab attendance is NOT optional. All labs are in Room
13 in DeGarmo. Think of the labs as scheduled homework time with a
tutor (your GA). If you do not attend a lab, you can still the submit
lab assignments with a 10% penalty. Since labs are worth 5 points, the
penalty is only half a percentage point of your final grade. Don't be
fooled, though. Getting many small penalties add up quickly and often
make the difference between 2 grades.
In lectures, from time to time, I
will ask
questions using the "Clicker" technology. You must give all your
answers in good faith (i.e., no random or deliberately misleading
responses). I will sometimes use your responses as data to illustrate
data analysis. If
the questions are about opinions or life history involving personal
matters you will always have the option of clicking "I prefer not to
answer this question." I will never look at any individual's response
to these kinds of questions nor will I penalize anyone for choosing not
to answer them.
Your class participation grade will be determined by the percentage of
times that you participated using the Clickers. I will allow 2
unexcused absences before it affects the participation grade. You may
make up classwork only if you were
absent due to University sanctioned events, documented illnesses, or
documented
crises. Make-up assignments will typically be short essays.
Do not use an absent classmate's Clicker to make it seem that the
student was in attendence. This is dishonest and will result in an
automate failing grade for everyone involved in the activity.
Additional Notes
Make-up quizzes or exams/projects are typically not given. Special
circumstances may result in reasonable substitutes for missed
assignments.
The course contract is considered final. The work necessary to
obtain
the grade you desire has been outlined here. No additional work will be
accepted to increase your grade. Do not come to me at semester's end
asking
if there is some additional work you can do to increase your grade. At
semester's end, there is none.
If You Need Help...
Please visit me during my office hours with any questions you have. My
job is to help you learn. If you need help, get it early; don't wait
until
you are "so lost I don't know what to ask!" If you cannot make it to my
regular office hours then, please, make an appointment with me. Talk to
me after class, call me (438-8410), or e-mail me at: wjschne@mail.ilstu.edu.
Extra assistance
Any student needing to arrange a reasonable accommodation for a
documented
disability should contact Disability Concerns at 350 Fell Hall,
438-5853
(voice), 438-8620 (TDD).
Evaluation
Your grade will be determined by weighting your performance on
homework,article
assignments, Mallard quizzes, in-class labs, 3 exams, and two projects.
- Class Participation:
Attendence in lecture will be taken by Clickers.
- Labs: Labs will include both group and individual
exercises. Each of
the labs will be described in a web page. Most of them will involve
submitting answers to your GA by email and/or WebCT
- Homework: Problems to be
worked on independently and submitted by WebCT.
- Exams: There will be three exams. They are cumulative to
the
extent
that the material from later parts of the class build upon material
from
the early parts. These exams may include both conceptual and
compuational
questions. The format will typically be both multiple choice and short
answer. Some portions of the exams will be closed books. More
information
will be given in class.
- Project: You will demonstrate an integrative
understanding of reasoning with statistics by proposing a hypothesis
and method of testing it using several methods. You will create fake
data and analyse the data as if it were real. You will write a short
paper to communicate your results.
The grading scheme is not a curve. This is a good thing. This means
that everyone can get an A if everyone performs well. Of course, this
means that everyone could fail the course if everyone blows it off. A
curve would make it so that only a certain percentage can receive high
grades and that certain percentage would fail the course no matter how
well they understand the material.
Each exam is worth a maximum of 150 points (3 Exams x 150 points =
450 total)
Each homework is worth 20 points (9 Homework assignments x 20 points =
180 total).
Each lab is worth 5 points (24 Labs x 5 points = 120 total).
The project is worth 150 points
Class Participation is worth 100 points
Therefore, there is a total of 1000 possible points. Your final
semester
grade is determined as follows:
Performance Grade
900-1000 A
800-899 B
700-799 C
600-699 D
0-599 F
Tentative Course Outline
| Class Dates |
Tentative topic calendar |
Things due |
| WK1 |
Aug. 20
|
Introduction and syllabus
review |
Lab
1 |
| Aug. 22 |
Lab
2 |
| WK2 |
Aug. 27 |
Measurement |
Lab 3
|
| Aug. 29 |
Frequency distributions |
Lab 4
|
| WK3 |
Sep. 3 |
Labor Day (No class, no labs)
|
|
| Sep. 5 |
Measures of Central Tendency |
Lab 5
|
| WK4 |
Sep. 10 |
Variability |
Lab 6 |
| Sep. 12 |
Normal Distribution |
Lab 7
Homework 1 (Due at 11:55pm)
|
WK 5
|
Sep. 17 |
Correlation |
Lab
8 |
| Sep. 19 |
Regression |
Lab
9 |
| WK6 |
Sep. 24 |
Exam 1 (Conceptual
part in lecture, computational part in lab)
|
Study
Guide
|
| Sep. 26 |
Basic Probability |
Lab 10
Homework 2 (Due at 11:55pm)
|
| WK7 |
Oct. 1
|
Sampling Distributions |
Lab 11 |
| Oct. 3 |
Null and Alternative Hypotheses
|
Lab 12 |
| WK8 |
Oct. 8 |
Hypothesis Testing |
Lab 13 |
| Oct. 10 |
Statistical Power |
Lab 14 |
| WK10 |
Oct. 15 |
Confidence Intervals
|
Lab
15
Homework 3 (Due at 11:55pm)
|
| Oct. 17 |
Effect Sizes
|
Lab
16 |
| WK11 |
Oct. 22 |
Review
|
Lab
17
|
| Oct. 24 |
Exam 2 (Conceptual
part in lecture, computational part in lab) |
Study
Guide
Link
to Spreadsheets
|
| WK12 |
Oct. 29 |
One-Sample t-test |
Lab
18
Homework 4 (Due at 11:55pm)
|
Oct. 31
|
Related samples t-test |
Lab
19
|
| WK13 |
Nov. 5
|
Independent samples t-tests |
Lab 20
|
Nov. 7
|
Which test?
|
Lab 21
|
| WK14 |
Nov. 12
|
Confidence Intervals with t-tests
|
Lab 22
|
Nov. 14
|
Regression and hypothesis testing |
Lab 23
|
| WK15 |
Nov. 26
|
Data analysis in the real world |
Work on Project
in Lab |
| Nov. 28 |
Data analysis in the real world |
Work on Project in Lab
|
| WK16 |
Dec. 3
|
Review for Computational/Lab Part of Exam 3 |
Work on Project in Lab
Homework 5 (Due at 11:55pm)
|
Dec. 5
|
Review for Conceptual/Lecture Part of
Exam 3
|
Computational Part
of Exam 3
Project Due (Due at
11:55pm) |
| Finals Week |
Dec. 13
|
Exam 3 (Conceptual
part in lecture at 7:50AM on Thursday, Dec. 13)
Study
Guide
|