data

Jason Newsom's USP 634
Data Analysis I
Spring 2011

Description

This course has an applied approach to statistical analysis and research methodology. The goal is to provide students with statistical background, conceptual understanding, technical writing skills, computer application, and the ability to apply these skills to realistic data analysis problems and research designs. Topics include review of undergraduate statistics, chi-square, correlation, t-tests, and Analysis of Variance for between and within subjects designs. Together with the second course (USP 654 Data Analysis II offered in the Fall term), this course will be a thorough and reasonably comprehensive introduction to understanding, critically evaluating, and conducting analyses for most studies in social science-related disciplines. Course requirements include three homework assignments using SPSS statistical software, two exams, and participation in the weekly SPSS lab. Prerequisites include an undergraduate statistics course and general familiarity with research design and methodology. Recommended (but not required) prior courses include USP 630 Research Design taught Fall term and USP 532 Data Collection taught by Margaret Neal Winter term.

Spring 2011 Syllabus
Class syllabus with the reading list and my contact information

Supplemental Readings

HW 3 Readings

Required

Optional

Current Homework
Get a copy of the current homework and link to the data sets.

Homework Data Sets
Get the data you need here

Lab Website
Kihong Kim, lab instructor: https://sites.google.com/site/uspda1lab

Review Sheets

Midterm

Final

Overheads and Handouts
(pdf format; sorry, not all overheads will be posted and handouts will only be
available after the material has been covered in class)

Basic Threats to Internal Validity

Some General and Technical Writing Suggestions

Overhead: Descriptive Statistics

t-test Hand Computation and SPSS Example

Within-subjects t-test

Levels of Measurement and Choosing the Correct Statistical Test

Single-Group Statistical Tests with a Binary Dependent Variable

2 X 2 Contingency Chi-square

Chi-square for within-subjects: McNemar's test

Correlation Example

t-Tests, Chi-squares, Phi, Correlations: It's all the same stuff

Reliability Analysis Example