APPLIED STATISTICAL ANALYSIS FOR
FAMILY STUDIES AND HUMAN DEVELOPMENT:
1. INTRODUCTION TO QUANTITATIVE ANALYSIS
FSHD 537a
FALL 2008 SYLLABUS
INSTRUCTOR:
Bruce J. Ellis, Ph.D.
Office: McClelland Park 315G
Phone: (520) 626-5703
Email: bjellis@email.arizona.edu
LAB INSTRUCTOR: Gabriel Schlomer, M.S.
Office: McClelland Park 315E
Phone: 621-6575
Email: schlomer@email.arizona.edu
OFFICE HOURS:
Bruce: By appointment.
Gabe: Mondays 9:00-11:00
CLASS MEETINGS: Fridays 8:30-11:00 in McClelland Park 202
LAB MEETING:
Fridays 11:30-1:30 in the McClelland Park student
computer lab (ground floor)
DESCRIPTION:
This course provides an introduction to the logic and
application of statistical methods for anlayzing data
pertaining to human behavior, development, and
relationships. Topics covered include data management
and screening; methods for describing and presenting data;
t-tests; analysis of variance; correlation/regression analysis;
and advanced application of multiple regression such as
hierarchical procedures, suppression, and moderator/
mediator analyses.
This is an applied course in statistics. Thus, the emphasis is
not on learning math (i.e., doing statistical analyses by
hand). Rather, the major objectives of this course are for
you to gain a conceptual understanding of relevant
statistical methods, learn how to implement these methods
on a computer using SPSS, interpret the SPSS output,
prepare summary tables and text, and communicate the
results of statsticial analyses using APA style.
EVALUATION:
Lab assignments: 12 @ 100 points each.
100% of grade. Final grade is based on average of your
grades on the 12 assignments. Normal grading scale
applies (i.e., A = 90-100%; B = 80-89%; etc.)
Lab assignments will generally involve performing statistical analyses using
SPSS, interpreting the output, writing results sections using Tables and/or Figures
and accompanying text, based on provided data sets. In the labs, you will learn
the commands necessary to complete the assignments on your own. The lab
assignments will be handed out each week in class.
LAB DUE DATES: Tuesdays, 5pm, under Gabe’s door (315E). Without prior
approval, 15 points will be deducted for each day (24 hour time period) that the
assignments are late. For instance, if you turn in your assignment 1 hour late, you
lose 15 points; if you turn it in 25 hours late, you lose 30 points, etc.
Class participation includes (a) being in class every week, being well prepared
by having carefully read all the assigned readings, (c) contributing actively to
critical discussion in class about the readings, and (d) participating actively in the
computer lab. Students are expected to come to class every week, on time, wellprepared, and ready to discuss the readings. If for any reason in any given week
students cannot live up to these expectations, I need to be notified in advance.
READINGS:
Assigned text
Field, A. (2005). Discovering statistics using SPSS (2nd
Ed.). (SPSS). London: Sage Publications. [In bookstore]
Jaccard, J., & Turrisi, R. (2003). Interaction effects in
multiple regression (2nd ed.). Thousand Oaks, CA: Sage.
Schroeder, L.D., Sjoquist, D.L., & Stephan, P.E. (1986).
Understanding regression analysis: An introductory guide.
Newbury Park, CA: Sage
Assigned readings in coursepack
Tabachnick, B.G., & Fidell, L.S. (2001). Using multivariate
statistics (USM), 4th ed. Boston: Allyn & Bacon. [Chapters
4-5]
Tabachnick, B.G., & Fidell, L.S. (2001). Computer assisted
research design and analysis (CARDA). Boston: Allyn &
Bacon. [Chapter 3]
Frazier, P.A., Tix, A.P, & Barron, K.E. (2004). Testing
moderator and mediator effects in counseling research.
Journal of Counseling Psychology, 51, 115-134.
SCHEDULE:
WEEK
Aug 29
READING
----------------
LAB ASSIGNMENT
-----------------------
SPSS
Chapters 1, 2
TOPIC
Introduction and
overview
Introduction to
Statistics
Sept 5
Sept 12
SPSS: Chap. 4
Correlations
2. Correlations
Sept 19
CARDA: Chapter 3
3. Basic Logic of ANOVA
[No stats lab]
Sept 26
SPSS: Chap. 7
Basic ANOVA: Logic
of analysis and tests of
assumptions
Comparing two means
Oct 3
UMS: Chapter 4
Oct 10
UMS: Chapter 4
Oct 17
SPSS: Chap. 8
Oct 24
Oct 31
1. SPSS basics
4. t-tests
Cleaning up your act:
Screening data prior to
analysis
Cleaning up your act:
Screening data prior to
analysis
Comparing several
means through
ANOVA
5. Cleaning up your act:
Part 1 [No stats lab]
SPSS: Chap. 10
Factorial ANOVA
8. Factorial ANOVAS
Schroeder et al.
(1986), pp. 12-22, 2932, 56-58.
UMS: Chapter 5 (up to
p. 130)
UMS Chap. 5 (p. 131
to end of chapter).
Multiple regression
9. Introduction to Regression
Analysis
[No stats lab]
Multiple regression
10. Multiple Regression
Nov 14
Jaccard et al. (2003),
pp. 16-43;
[No homework or stats lab]
-------------------------------
Nov 21
Frazier et al. (2004),
pp. 115-125.
Multiple regression:
regression interactions
(Gabe’s lecture)
Multiple regression:
regression interactions
Nov 28
------------
Thanksgiving Break
Dec 5
Frazier et al. (2004),
pp. 125-132.
Multiple regression:
Mediational analysis
Nov 7
6. Cleaning up your act:
Part 2
7. One-way analysis of
variance, fixed-effects
designs
11. Interaction effects in
Regression
12. Mediational analysis
through multiple regression