University of Baltimore Division of Applied Behavioral Sciences
Intermediate Statistics for the Behavioral Sciences
APPL 631.185 (class no. 2469)
Instructor: Tom Mitchell,
Ph.D. 410. 837-5348
Home Page: http://home.ubalt.edu/tmitch
Office Hours (Academic
Center 209 D):
Mondays & Tuesdays
12 - 2:00
Class: Tuesdays 5:30 - 8:00 PM Room AC 235
Websites for Psychology
Association for Psychological Science
Psychological Research on the Net (APS)
Psychological Journals Online (Hanover College)
Cozby, P. C. (2001). Methods in behavioral research. (7th edition). Mountain View, CA: Mayfield.
SPSS helper (UCLA)
Research Methods Tutorial
Sources attached to this syllabus:
Pocket calculator: calc.exe
UB Academic Resources Center: (for help with math and statistics):
American Psychological Association (1995) Publication manual of the American Psychological Association
Using APA format for manuscripts
APA Style.org (tips on style)
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.
Gravetter, F. J., & Wallnau, L. B. (2009).
Statistics for the behavioral sciences (8th ed.). Belmont,
Learning. ISBN: 9-780-495-60220-0
Optional: APA (2001). Publication Manual of the American Psychological Association, 5th edition
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).
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
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
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
Chapter 17: Introduction to Regression (bivariate only p. 563-580) Multiple Regression: G. David Garson North Carolina State
***** March 16 Spring Break ************* ski the Rockies
Week 8: March 23
Chapter 9: Introduction to the t statistic p. 280
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
Cozby Chapter Factorial designs Erwin Segal, Buffalo
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
Other online resources:
Effect size calculator ( Becker)
G. David Garson North Carolina State
Interrater reliability and agreement Excel file
StatSoftInc.com Multiple Regression