Designed as a two-semester sequence for doctoral students, this course introduces students to the tools of data analysis using SPSS for Windows. Emphasis is on the acquisition of conceptual understanding over computational skill. Particular topics covered are listed in the course outline.
Professor: Sharon L. Weinberg
office location: 12th Floor, Bobst Library
office hours: Mondays, 2 to 3 pm
Teaching Assistant: Eileen Rodriguez
Except where noted on the curriculum outline, E10.2001 meets on Mondays from 3:30 to 6:00 pm.
As a student in this class you have priority access to the computer labs which means that you may enter the lab at any time by swiping your ID. The regular lab consultants often do not know SPSS, but they can answer system level questions about accessing SPSS, and saving, printing, and opening files. At Tisch LC8, there are two statistics consultants during the day who know SPSS quite well.
The text Data Analysis for the Behavioral Science using SPSS by Sharon L. Weinberg and Sarah K. Abramowitz, Cambridge University Press, 2002 is available at the NYU Bookstore.
Homework: Practicing what has been covered in class is essential to learning statistics. Homework will be assigned, collected, and graded each week. All students are responsible for completing all homework assignments on time and raising related questions in class.
Project: Students will be expected to complete a project that requires the selection of appropriate statistical methods to answer a series of questions based on a given data set made available by the instructor and to interpret and communicate findings in a cogent manner.
Exams: There will be one midterm and one cumulative final.
Grade Composition: Homework: 15% Midterm: 25% Final Exam: 25% Project: 35%
Course Outline: E10.2001 .
Day Topic Discussed in Class
09/10 Overview & introduction to SPSS: Chapter 1
09/17 No class: Rosh Hashanah Holiday
09/24 Examining univariate distributions: Chapter 2
10/01 Measuring location, spread, and skewness: Chapter 3
10/08 Transforming data: Chapter 4
10/15 Bivariate relationships: Chapter 5
10/22 Simple linear regression: Chapter 6
10/29 Review for Midterm: Chapters 1 through 4
11/05 MIDTERM: Includes material through Chapter 4
11/12 Review Midterm; Introduction to inferential statistics: Chapter 7
11/19 Foundations of inferential statistics continued: Chapter 7
11/26 Foundations of inferential statistics: Chapter 8
12/03 Foundations of inferential statistics: Chapter 9
12/10 LAST CLASS. PROJECT DUE. Review for Final.
12/17 FINAL EXAM: Includes all material covered during the semester