Jason Newsom's
USP 634 Data Analysis I
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 2013 Syllabus
Class syllabus
with the reading list and my contact information
Supplemental Readings
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Current Homework
Get a copy of the current homework and
link to the data sets
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Homework Data Sets
Get the data you need here
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Lab Website
https://sites.google.com/a/pdx.edu/usp-634-data-analysis-i-spring-2013/
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Review Sheets
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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
Overhead:
Descriptive Statistics
t-test
Example: Hand Computation and SPSS
Within-subjects
t-test Example: Hand Computation and SPSS
Overheads:
Sampling Distribution and t-distribution
Levels of
Measurement and Choosing the Correct Statistical Test
Single-Group
Statistical Tests with a Binary Dependent Variable
Some General
and Technical Writing Suggestions
Chi-square
for within-subjects: McNemar's test
Overhead:
Connection Between Binomial and Normal Distributions
Overhead:
Scatterplot of Hypothetical Test Score Data
Overhead:
Correlation Problems
Correlation
Example: Hand Computation and SPSS
t-Tests, Chi-squares, Phi, Correlations: It's all the same
stuff
Reliability
Analysis: SPSS Example
ANOVA
Example: Hand Computation and SPSS
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Stats Notes
Over 20 "Web
lectures" on introductory graduate statistics
Links
William Trochim's Outstanding Research Methods Knowledge Base
UCLA
Statistical Computing Site on using SPSS
MacTutor History of Mathematics and Statistics
Interactive
Statistical Demonstrations