IPC
542 Statistics
Summer Trimester 2000
Section 1:
Tues. 5:30 – 8:00 p.m., Y205
Section 2:
Tues. 8:00 – 10:30 p.m., Y205
Instructor: Kurt Monroe
Telephone: 618-453-7635 (office)
618-457-7463 (home)
E-mail: kmonroe1@siu.edu
Required texts: Moore, D. S. (1995). The Basic Practice of Statistics. New
York: W. H.
Freeman and Company.
Holcomb, Z. C.
(1998). Interpreting Basic
Statistics. 2nd ed.
Los Angeles,
CA: Pyrczak Publishing.
Reference texts: SPSS
Inc. 1997. SPSS Base 7.5 for Windows User Guide.
Chicago, IL:
Author.
Gay,
L.R. (1999). Educational Research.
6th ed. Englewood
Cliffs,
NJ: Prentice-Hall.
Student Learning
Objectives:
This course will be taught while keeping two (2) major
objectives in mind. The first goal is
to prepare you for the section of the Licensed Professional Counselor exam that
pertains to research and evaluation (i.e., statistics). As many of you may be aware, several mental
health disciplines (e.g., family counselors, psychologists, social workers,
etc.) require an examination at certain stages of one’s professional
development. Such an examination is the
National Counselor Examination (NCE).
Those who pass this or a similar exam are called Licensed Professional
Counselors (LPC), however some states may use a different title. Nevertheless, to pass this exam you must
demonstrate a good understanding of statistics. That is where this class comes in. My class lectures will be structured and presented in such a way
as to equip you with the necessary knowledge to do well on the statistics
portion of the licensing exam.
The second objective of this course is to prepare you for
writing and analyzing data for your thesis.
“Doing” statistics for a master’s thesis is a real psychological
obstacle for many graduate students. I
hope that such anxiety will be lessened during or after this course. In addition to learning how to analyze,
interpret, and report data, students will learn, in a step-by-step fashion, how
to develop and structure their master theses.
In short, students in this course will be able to:
1) Demonstrate an understanding of basic concepts,
descriptive statistics, and inferential statistics, such as chi-square,
t-tests, correlation, and regression analysis.
2) Display the ability to formulate hypotheses, both
symbolically and in words, and understand various methods of testing
hypotheses.
3) Demonstrate an understanding of SPSS (a statistical
package for the social sciences) by generating a data set, including variable
names, performing the appropriate statistical procedure(s), and interpreting
the output.
4) Develop and piece together various sections of a
thesis, such as the introduction, literature review, and methodology.
The aforementioned capacities
should give you the basic skills to compose and run statistics for your
master’s thesis as well as understand some statistical procedures employed in
the professional literature.
Course Requirements:
During
the course of the semester you will have the opportunity to conduct two
statistical analyses using data I provide, data from your own research that you
have collected yourself, or data that you have generated. Many of you may prefer to use the data sets
I provide. However, I want to afford
you the opportunity to analyze data that pertains to a topic of interest. These analyses will parallel the statistical
techniques we discuss in class. Each
statistical analysis will be written up in the form of a journal article using
the following format:
1. Introduction:
The
purpose of this section is to provide a brief history or explanation for why
you are investigating this problem.
Discuss the general significance of this area of research, and why it is
important to you in particular. Then,
in clear and unambiguous language, state the research problem.
2. Literature Review:
This
does not have to be more than a paragraph or so, and may be entirely made up if
you are using a “contrived” research problem.
Briefly describe what research, either directly or indirectly related to
yours, has been previously conducted that helps to shed light on your
particular question. Perhaps you may
wish to discuss deficiencies in previous research that lead you to address this
particular research question. Conclude
by stating your hypothesis (in words and symbolically) and define the variables
operationally. For example, it is usually most suitable to state the null and
alternative hypotheses here.
3. Procedures:
In
this section, describe your procedures in enough detail so that someone reading
your description has a sense of how the experiment can be replicated. Also, briefly discuss subjects and
instruments employed.
4. Results and Discussion:
a. The results are just that, results. Report all pertinent statistics such as
correlation coefficients and R˛ values, chi-square, t, and corresponding p
values, degrees of freedom, etc. Tables
are a good way to represent this kind of information. In this section, each hypothesis or sub-hypothesis should be
addressed separately. State your decision
with respect to each null hypothesis, and report the required statistics.
b. Discussion/conclusion: The results do not occur in a vacuum. Relate your results back to your research question and your
literature review. (restating the results does not count as a discussion or
conclusion). How has your research
added to the body of literature that already exists on the subject? What is the significance of your
results? This only needs to be a few
sentences, but it is a very important part of the final product.
Later
in the trimester I will provide you with a sample analysis and write-up as an
example of incorporating the above five steps.
I will also model in class each of the computer analyses, demonstrating
how to analyze data using SPSS and identify pertinent output.
Throughout the course students will learn how to develop various
sections of a thesis. Combining lecture
material from both Research Methods and Statistics, students will learn how to
structure the following sections of a thesis:
1. Introduction (task 2) – want to be good for thesis
2. Literature review (task 3) – outline only.
3. Subjects (task 4)
4. Instruments (task 5)
5. Procedures (task 6)
Each
task will be assigned based on when the material is cover (see due dates). I will critique each task and return
them. Then at the end of the semester
students are to make the appropriate corrections and consolidate the five
sections into one large paper, which will be your research proposal. You will receive one (1) point for turning
in each task on time (totaling 8 points) and can possibly earn a total of 32
points for the final draft of the research proposal. Please attach the critiqued sections at the end of the final
paper. This process will be discussed
more during class.
The
objective of the homework is for you to apply the material discussed in
class. For the class assignments you
will all be divided into groups, and for the computer assignments, you may also
have to work in pairs or threesomes. I
am hoping that each of you will have the opportunity to complete the computer
lab projects on your own so that you may become familiar with SPSS. However, we may have to make due with what
we get. Even though you will be working
in groups, each of you will turn in the assignment at the end of class or at
the beginning of the next class period.
Each of you will have the opportunity to correct any mistakes so that
you can receive full credit. Corrections
are due the week after the homework is returned.
IV. Quizzes (10 Points total)
There
will be approximately 3 to 4 quizzes throughout the course of the
semester. My experience teaching this
course has shown me that if students are not forced to look at their notes,
they tend not to learn. Therefore, I
will have small quizzes covering some of the most crucial material, such as
levels of measurement, tests of significance, interpreting statistics (e.g.,
p-values, t-values, etc.), and interpreting output from SPSS.
Evaluation:
Points Grade
80 – 89 B
70 – 79 C
The
points you earn in this course will be added to the 100 possible points from
research design, resulting in one grade for both courses. I will discuss grading more during class.
Reading Assignment and
Lecture Schedule (tentative):
May 9 Introduction
May 16 Basic concepts and descriptive
statistics
Readings: Moore, Ch. 1
1st article due
May 23 Descriptive statistics (continue)
Readings: Moore, Ch. 1
last 2 articles due
May 30 Normal and Sample distributions
Readings: Moore, Ch. 1.3, 4.1, 4.3
task 4 due for my second section
June 6 Estimation, hypothesis writing and testing, and
Confidence Intervals
Readings: Moore, Ch 6
task 4 due for my first section
task 5 due for my second section
June 13 T-tests
(i)
one-sample
(ii)
matched/paired samples
Readings: Moore, Ch. 7.1
task 5 due for my first section
June 20 T-tests
(i)
independent t-tests
Readings: Moore, Ch. 7.2
task 2 due
June 27 Correlation
Readings: Moore, Ch. 2.1 and 2.2
July 4 Independence day (no class)
July 11 Correlation (cont.)
first computer assignment due
July 18 SPSS project 1
(computer lab)
task 3 is due – outline of literature
review
July 25 Two-way tables and the chi-square
test of independence
Readings: Moore, Ch. 9 and 2.5
Aug. 1 SPSS project 2
(computer lab)
task 6 is due AND late submission date for
tasks 4 & 5
Aug. 8 Finish up
chi-square test of independence and review of course
Aug. 15 Final proposals due/ Presentations
second computer assignment due
Attendance Policy:
I will employ the conditions
of the Lindenwood attendance policy for this class. This means that four (4) or more absences will result in failing
the course. If you miss more than
two (2) classes, your grade will be reduced by one letter. In other words, you will be afforded two (2)
absentees. I understand that most of
you work full time and emergencies arise, so please contact me (preferably by
e-mail) and let me know if you will be missing class. It will be your responsibility to get notes or homework from
classmates.
Accommodations:
If you have a learning or
physical disability, please let me know so that your needs may be
accommodated.