COURSE SYLLABUS:

Intermediate Statistics for the Behavioral Sciences

APPL 631.185 (class no. 2469)

Spring 2010

Instructor: Tom Mitchell, Ph.D. 410. 837-5348

Email: TMITCHELL@ubalt.edu

Office Hours (Academic Center 209 D):
Mondays & Tuesdays
12 - 2:00

Class: Tuesdays 5:30 - 8:00 PM  Room AC 235

WebTyco

Websites for Psychology

Pocket calculator:  calc.exe

ONLINE Calculator

I. Course Information
A.  Catalog description:  The logic of hypothesis testing and assumptions underlying its use are the framework for studying analysis of variance and covariance and multiple regression. These tools are learned in the context of application to psychological research. Students learn to complete statistical analyses using a microcomputer statistical package and to interpret the results.

B.  Course description: This course will provide a detailed description of fundamental research methods with their associated statistical procedures.

II. Objectives of course:

§  The purpose of this course is to help you understand how statistics, as scientific tools, help researchers answer scientific questions. Please do not be overly concerned if you do not remember very much from your previous statistics course(s). This is actually quite typical. Because students arrive at graduate school with various degrees of exposure (and confidence) with statistics, we will be starting at the beginning. This course will be much like an advanced version of an introductory undergraduate statistics course, covering the same topics – descriptive statistics, hypothesis testing, t-tests, chi-square, correlation, and analysis of variance among them - but in somewhat greater depth.

§  One central purpose of this course is to prepare students to interpret data from real research. You, as students, will frequently provide the data for us to analyze in class. Research indicates that individuals process information more deeply when it is personally meaningful to them. Research also shows that nothing is more personally meaningful to people than themselves ;) so you will act as participants on a few occasions.

§  We will primarily tackle statistics at a conceptual level. We will utilize both hand-calculations and computer analyses (SPSS) for most of the computations in this course, but you will be in a stronger position to excel on the exams if you understand what various statistical techniques do and what they mean. I do not require students to memorize formulas in the class, but the exams will necessitate a sophisticated knowledge of the purpose and appropriate application of various statistical techniques.

III. Learning Objectives:  Students will:

§  develop greater understanding of the various statistical techniques utilized in psychological research

§  increase their competency for selecting appropriate statistical techniques (when, for example, an independent-samples t-test is used)

§  learn how to conduct these statistical techniques through the use of a computer-software package (SPSS)

§  increase their critical thinking about scientific research

§  Students will enhance their ability to write APA-style results sections

IV.  Class format: Assigned material will be discussed and clarified. Class time will also be used to discuss SPSS applications.

V. Texts for course:

Required: Gravetter, F. J., & Wallnau, L. B. (2009). Statistics for the behavioral sciences (8th ed.). Belmont, CA: Wadsworth/Thomson
Learning.  ISBN: 9-780-495-60220-0

Optional:  APA (2001). Publication Manual of the American Psychological Association, 5th edition

VI. Assessment: (each component is graded on a 100 point scale:
A (90-100), B (80-89), C (70-79), F (<70)

Exams: Three exams (multiple choice and short answer) 30 % each exam

Homework assignments: (to be turned in for week chapter is covered) 10%
1. complete odd numbered Problems at end of each assigned chapter
2. SPSS assignments

Notes: If you expect to miss a class, it your responsibility to make sure you get notes or  handouts and changes in assignments.
*** Assignments turned in late will result in a reduction in grade points ****

Class attendance and submission of assignments is essential. Failure to submit assignments when due may result in a decrement of your grade.

Policy on Academic Integrity (Plagiarism): see more detail at Plagiarism (Tulane)

"Plagiarism is the intentional or unintentional presentation of another person's idea or product as one's own. Plagiarism includes, but is not limited to the following: copying verbatim all or part of another's written work; using phrases, charts, figures, illustrations, or mathematical or scientific solutions without citing the source; paraphrasing ideas, conclusions, or research without citing the source; and using all or part of a literary plot, poem, film, musical score, or other artistic product without attributing the work to its creator. Students can avoid unintentional plagiarism by carefully accepted scholarly practices. Notes taken for papers and research projects should accurately record sources of material to be cited, quoted, paraphrased, or summarized, and papers should acknowledge these sources in footnotes." (Anonymous).

Chapters assigned and anticipated dates of Exams:

Week & Date Assignments

Week 1: Jan 26

Review of Syllabus
Chapter 1: Introduction to Statistics p. 1
Review of Descriptive and Inferential Statistics, Experimental Method, and Scales of Measurement

Scales of Measurement ppt.

Week 2: Feb 2

Chapter 2: Frequency Distributions p. 35 Questions: 13, 15
Chapter 3: Central Tendency p. 70 Questions: 4,5,9,12,18,25,26

Week 3: Feb 9

Chapter 4: Variability p. 104  Variance calculator/linear regression/correlation calculator  Questions: 2,3,5,9,12,18,25,26,

Chapter 5:  z Scores: Location of scores and Standardized Distributions p. 137 Questions:
5,7,11,13,15,19,21,23

Week 4: Feb 16

Chapter 6: Probability p. 163 Questions: 3,5,7,14,17,21,
NOTE: omit Probability and the binomial distribution, p. 183-188.

Week 5:  Feb 23       Exam One: Chapters 1-6

Week 6:  March 2

Chapter 7: Probability and Samples: The Distribution of Sample Means p. 198  Questions: 2,4,5,7,10,12,15,19,22
Chapter 8: Introduction to Hypothesis Testing p. 229 Questions: 2,4,5,6,8,11,13,15,19
Relations between alpha, beta, power

Week 7:   March 9

Chapter 16: Correlation p. 519  Guess Correlation Questions: 8,13,14,18
Chapter 17: Introduction to Regression (bivariate only p. 563-580)  Multiple Regression: G. David Garson North Carolina State
Questions: 2,5,6,7,15

***** March 16 Spring Break ************* ski the Rockies

Week 8:   March 23

Chapter 9: Introduction to the t statistic p. 280    Effect size indicators (Becker at UCCS
Chapter questions: 1,2,3,7,10,22

Week 9:   March 30

Chapter 10: The t-test for Two Independent Samples p. 307  chapter questions: 1-6, 14, 25

Week 10: April 6

Chapter 11: The t-test for Two Related Samples p. 339  Chapter questions:1-5, 8, 15

Week 11:  April 13     Exam Two: Chapters 16, 17, 9, 10, 11

Week 12: April 20

Chapter 13: Introduction to Analysis of Variance p. 392    Chapter 13 questions: 1-5, 7, 11, 15,18, 22

Week 13: April 27

Chapter 15: Two-Factor Analysis of Variance (Independent Measures) p. 477 Chapter questions: 4, 5, 6, 7, 9, 11

Week 14:  May 4

Chapter 18: Chi Squared Statistic: Tests for Goodness of Fit and Independence p. 644  Chapter questions: 1, 2, 9, 15, 23
Fisher's exact test for small expected values

Week 15: May 11  Exam three: (final) Chapters 13, 15, 18