Advanced Statistics
PSYSC 342 - Spring 2009
Instructor: Dr. Thomas Holtgraves
NQ 108B
285-1716
E-Mail: 00T0HOLTGRAV@bsu.edu
Office Hours: MW 4:00: - 5:00 /By appointment
Webpage: http://www.bsu.edu/web/00t0holtgrav/
Required texts:
Green, S. B., & Salkind, N. J. (2008). Using SPSS for Windows and Macintosh (5th edition). Upper Saddle River, NJ: Pearson Prentice-Hall. Packages with SPSS (time limited) software.
Howell, D. C. (2004). Fundamental statistics for the behavioral sciences (5th edition). Belmont, CA: Brooks/Cole.
Course Goals: The overall goal of this course is to provide students with advanced training in statistical
techniques, with an equal emphasis on application and theory/conceptualization. In terms of the latter, we will
first review basic statistical concepts and techniques presented in PSYSC 241. Then, the remainder of the
course will involve a consideration of more advanced techniques including: factorial ANOVAs, repeated
measure ANOVAs, mixed model ANOVAs, regression analysis, reliability analysis, and factor analysis. In
terms of application, a major part of the course will involve learning to use SPSS to conduct statistical analyses.
The applied and conceptual aspects of statistics will be interwoven. That is, students will learn the conceptual
underpinnings of statistical tests as well as how to conduct those tests using the SPSS for Windows program.
Course Format: Class time will be used for presenting statistical concepts via lecture, and for working through
statistical problems using SPSS. During class, students will have available to them a laptop computer for use in
working through the problems. It is, of course, recommended that students keep up with the material. More
than many courses, this course is truly cumulative; what is presented later in the course will require familiarity
with what was presented earlier in the course. In other words, to do well in the course you need to keep up with
the material.
Disability Adaptations and Accommodations: If you need course adaptations or accommodations because of a
disability, if you have emergency medical information to share with me, or if you need special arrangements in
case the building must be evacuated, please make an appointment with me as soon as possible. My office
location and hours are listed above.
Statement of Academic Honesty: For learning to be meaningful and worthwhile it must be based on honesty. Learning that is not fundamentally honest is incomplete, systematically flawed and potentially damaging to all of us. Simply put: if you cheat, you don't learn. Academic dishonesty, or cheating, damages students and universities because it adds suspicion and resentment to academic competition, and it distorts the meaning of grades. Ball State University has taken a very definitive position on academic dishonest, as laid out in Section VIII.B of the Code of Student Rights and Responsibilities. Academic dishonest, as defined in the Code, includes, but is not limited to, using unauthorized aids during a test, submitting another's work as your own, and submitting previously presented work as newly executed work without my knowledge or authorization. I am committed to assigning grades based on students' honest efforts on exams and other class assignments. All suspected incidents of academic dishonesty will be pursed through the established channels.
Exams: Exams will constitute 2/3
of the final grade. There will be both in-class (1/3 of final grade) and
take-home (1/3 of final grade) exams.
Homework: Homework will be assigned regularly. Scores on homework assignments will constitute 1/3 of the final grade.
Course Outline
| Topic | Readings |
| Creating and editing SPSS data files | G & S Units 1 and 2 |
| Basic concepts | Howell chapters 1 and 2 |
| Describing data | Howell chapter 3 |
| Measures of central tendency and variability | Howell chapters 4 and 5 |
| Normal distribution | Howell chapter 6 |
| SPSS data description | G & S unit 4 G & S unit 5 lessons 20 and 21 |
| Probability and hypothesis testing | Howell chapters 7 and 8 |
| SPSS transformations | G & S lessons 13 and 19 |
| One sample t-test | Howell chapter 12 G & S unit 6 - lesson 22 |
| Exam 1 | |
| Two related sample t-tests | Howell chapter 13 G & S unit 6 - lesson 23 |
| Two independent sample t-tests | Howell chapter 14 G & S unit 6 - lesson 24 |
| One-way ANOVA | Howell chapter 16 G & S lesson 25 |
| Factorial ANOVA | Howell chapter 17 G & S lesson 26 |
| Power | Howel chapter 15 |
| Exam 2 | |
| Repeated Measures ANOVA | Howell chapter 18 G & S lessons 29 and 30 |
| Correlation | Howell chapter 9 G & S lessons 31 and 32 |
| ANCOVA | G & S lesson 27 |
| Regression | Howell chapters 10 and 11 G & S lessons 33 and 34 |
| Nonparametric techniques | Howell chapters 19 and 20 C & S unit 10 |
| Exam 3 |