Approved by Faculty Senate Dec 3, 2001
University Studies Course Approval
Course Number: 231
Semester Hours: 3
Frequency Offered: Every Semester
Catalog Description: An overview of the theories, procedures and applications of descriptive, correlational and inferential statistics in the behavioral sciences. Topics include central tendency, variability, correlation, special correlational procedures, linear regression, parametric and non-parametric tests of significance. Prerequisite: PSY 210 and completion of Math/Stats basic skills requirement. Offered each semester.
A2C2 Approved Course? Yes
Requested Approval: Math/Statistics Flag
Contact Person: Richard Deyo, email@example.com
Description of the course requirements and learning activities that promote students math/statistics abilities.
a. Practice the correct application of mathematical or statistical models that are appropriate to their prerequisite knowledge of those areas.
The course is divided into three levels designed to build on the skills learned in the previous level. The assignments and topics are progressive in that each subsequent level builds on the concepts of the earlier in both content and in the demands placed on the students computational and inferential abilities.
In the first level, we develop an elementary ability to identify basic research designs toward the goal of learning to match the appropriate statistical model to the correct research design. Then building on these concepts (and the skills acquired in their basic math course) students are taught hypothesis construction, the rationale and methods for calculating descriptive statistics, distribution and sampling theory. At this level, all calculations are done without the aid of the computer to continue to develop students math skills and understanding of the computational basis for each statistical concept.
In the second level, we build on these concepts to practice and learn simple inferential models of statistical analyses. At this level, calculations are still made by hand as is appropriate. The models in this unit include Pearsons r, t-tests and one-way ANOVA with post-hoc tests. These models require considerable practice in interpreting the results of inferential tests. So we also spend considerable effort learning to write appropriate conclusions using standard methods of reporting statistical analyses (in the style used by most peer-reviewed journals).
In the third level, we further expand on the students ability to apply the most appropriate statistical model for the research design. However, at this level the calculations are usually extensive. For this reason we use computers for the calculations at this point in the course. The focus, however, remains on developing an understanding of why the computations are completed and their theoretical justification. We use this opportunity to also begin to teach the use of computers to construct graphs. The concepts in this level include multifactor ANOVA, repeated measure designs and nonparametrics.
b. Make proper use of modern mathematical or statistical methods appropriate to their level of prerequisite knowledge, to include, if statistics is used in a substantive way, the use of a statistical package with graphics capability when appropriate.
We plan to use a statistics package that can be used within the laptop program to illustrate statistical methods too extensive to be calculated by hand as discussed above in our third level of development. Statistical software packages are widely used in the industry, government, and university settings which would employ the majors of most of the students who currently enroll in this course. Training in a statistics and graphics program will enhance the practical computing skills of our graduates.
(note the syllabus for this course is distributed online hence the link references)
Dr. R. Deyo
Psyc 231 "Statistics"
Office: Main Campus: Phelps Hall Room 219A
Meet in Phelps 101 from 2:450 PM Mondays
Office Hours: Click here to see current schedule of office hours. Office hours are
subject to change based on student demand and use.
ClassNotes for 231: Click here to see a description of the current assignment or test topics. Check the class notes frequently during the term.
Study aids: Click here to find old versions of my midterms and final exams and
other study aids and practice problems.
Text: BASIC STATISTICS, 7th edition; Brooks Cole pub.: Author: Chris Spatz
Lab Book: Psychology Videolab Series Lab 2: "The effects of naloxone on social play behaviors
in the rat."; Allyn & Bacon pub.: Author: R. Deyo
In addition, you will need to have at least 20 sheets of graph paper and a ruler/straight edge.
A non programmable calculator is permitted in class and can be used in exams.
This is a Math/Statistics Flag course in the University Studies Program. As such, it includes requirements and learning activities that promote the students abilities to:
Course Description: The purpose of this course is to provide you with the theoretical and
computational background necessary for developing an understanding of the applications of
statistics as a research tool in the behavioral and life sciences.
This description sounds boring. So, why should I have to take this class?!!! OK, let's admit it. The
only reason many of you are here are because your major requires this class. You may be asking
Why, why, why? or WHY!
There are many reasons. Which of the following do you think is the correct answer?
a.) Most department chairs are sadists and want to torture you.
b.) You have to pay your dues.
c.) You are entering a profession that makes decisions based on research.
d.) both a and b.
The correct answer is C. For example, if you want to be a clinical psychologist, nurse, social
worker or a teacher you will probably work with a child that has ADHD at some point in
your career. Do you recommend methylphenidate? Do you use behavioral intervention? Perhaps
both? How do you know what to do? The answer is statistics. Statistics are reported in research
papers and published in professional journals as a way of communicating to professionals the
effectiveness of new treatments and how they compare to old methods. Understanding statistics
is required to understand how knowledge is obtained in your profession. In other words, to help
you make an informed decision.
Example: How did Prozac get to be the most prescribed antidepressant?
a.) It is common knowledge.
b.) Using statistics Prozac was shown to be more effective than the old standard called
c.) Using statistics Prozac was shown to have fewer side effects than the old standard called
d.) It was approved by the FDA.
a.) please think again.
d.) is true, but many antidepressants have been approved by the FDA that are better than Prozac
at reducing depression.
b.) is false. Prozac has never been shown to be more effective than imipramine which is still
(statistically) the most effective antidepressant
c.) is the correct answer. Imipramine produces some nasty side effects that are statistically
unlikely with Prozac. For example, the odds of getting a very aversive form of dry mouth and/or
constipation is 60 in 100 or 60% with Imipramine, but less than 2 in 100 with Prozac. Certain
statistics tell us that this difference is meaningful. By the way, dry mouth and constipation are the
number one reasons why people stop taking imipramine.
Grading & Tests: There will be weekly quizzes (20 pts each) that will be held on the first class
session of the week, a midterm (100pts) and a comprehensive final exam (100 pts). Each test or
quiz may consist of multiple choice, applied problems, short answer and/or an occasional essay.
In addition, there will be several assignments worth about 100 points (or more) from the lab
experiment. You will be allowed to drop your lowest quiz score. Course grades will be assigned
as follows: A= 90%, B= 80%, C=65% and D 55%.
All tests and quizzes are open notes and open book. Some quizzes will be take
home. Calculators are allowed if not programmable. Laptops may not be used
Missed Exams and classes: A quiz may not be made up for any reason. If you need to miss a
quiz it will serve as your lowest score and will be dropped. If you miss the midterm, you can
make it up on grading day (see below). No excuse is required just show up ready to go. If you
miss a class it is your responsibility to get the notes from someone in class (and not from me-I
lecture once). Please note that if an assignment is due, it is due at the beginning of class.
Anything turned in late will have 25% deducted for every 1/2 day that it is late. Anything turned
in under my door is automatically thrown away. Anything turned into my mailbox is dated when
I find it-not when you turned it in. So if I don't find it for a day its downgraded by 50%. YES
EVEN IF YOU PUT IT IN THE MAILBOX ON TIME. WHY? The only way I can keep track
of all of the assignments is if I get them all at once. Papers turned in under the door have been
thrown away by janitors and in some cases blow under my desk and have been found months
later. Papers turned in via my mailbox can get mixed up in other paperwork and lost. If you turn
your assignment in during class it will be placed with the other assignments and make everyone's
life easier. Remember you are preparing to enter a profession and professionals do not
Topic & Reading List
Topics for weeks 1-14 apply to University Studies goal A and topics for weeks 12 to the end of the semester apply to University Studies goal B.
Week1 Introduction to Experimental Design T: 1, LB: p 1-9 & handouts
Week 2 Complete In-Class Experiment pp-11-30
Week 3 Remember Weekly quizzes begin here!
Descriptive Statistics & Graphing T: 2, LB: 31-40
Week 4 Measures of Variability and z scores T: 3-4
Week 5 Determining Relationships between variables T: 4
Regression and Prediction
Week 6 Probability theory, Sampling & Distributions. 6,7 & handout.
Week 7 Distributions continued and Review for midterm (time
Week 9 Inferential Statistics- the t- test
Hypothesis testing : Part 1 t-tests T: 8-9, LB: 41-45
Week 10 Inferential statistics Part 2: ANOVA One-way T: 10
Week 11 Post-hoc tests handouts
Week 12 ANOVA Multifactor or Factorial Designs T: 11 and Computer Packages. Read the handout on using the statistical package selected for this semester. From this point on we will use the computers in 206 for our calculations and graphics.
Week 13 ANOVA Repeated and Correlated designs T: 12
Week 14 Chi square & Nonparametric Statistics T: 13-14
Week 14-end Applying Statistics T: 15
T=text or Spatz and LB= lab book
Important Dates & Notes
Labor Day Holiday No Class 9-3-01
Midterm Exam Monday October 15, 2001
Vetran's Day Holiday No Class 11-12-01
Final Exam Wednesday December 12, 2001 from 10:30-12:30 (it may not be
Make-up day Friday December 14, 2001 at 10:00 AM Phelps 219