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Data Science and Analytics

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SPSS Short Course

Course Materials Supplemental Materials
Part I: Introduction  

Module 1: Basic introduction to SPSS.

     Creating and importing data

Module 2: Graphing.

     IDA graphing and frequency charts

Module 3: Getting Descriptive Statistics.

     Descriptive statistics and the Explore Function

Module 4: Recoding an item.

     Recode Sex (from 1 = Female, 2 = Male into 0 = Female, 1 = Male)

     Recode Recall 1 using quartiles.

     Recode a 5-point Likert response scale if it is reverse coded to begin with

SPSS User Manuals in Adobe.pdf  

SPSS Home

Don't want to pay for SPSS? Then get PSPP for free!! PSPP is extremely similar to SPSS; but free!

Research and Statistical Support statistical resources workshop

Fairly comprehensive comparison of just about all statistical software packages: Wiki

An esteemed former colleague's collection of materials for the courses he taught.

Need to calculate a-priori power/sample size? Check out Gpower (it's free).

Link which will allows SPSS users to download the Legacy Viewer for viewing older SPSS files.

Part II: Intermediate Part III: Advanced (some commonly used analyses)

Module 5: Compute (simple)

     Create an average of Recall 1 and Recall 2

     Use the Compute Function to recode a Likert response scale item

     Use Compute to create a total score of multiple variables.

Module 6: Replace Missing Values

     Multiple Imputation using a version of the EM algorithm

Module 7: Select cases (create a filter variable).

     Select only sophomores in 'ExampleData002.sav'

Module 8: Merge data files.

     Add ‘ExampleData002.sav’ to ‘ExampleData001.sav’ to add cases

     Merge 'ex3reverse.sav' and 'ex3r2.sav' to add new or additional variables

     Restructure data from Long format to Wide format

ExampleData001.sav ExampleData002.sav ex3reverse.sav ex3r2.sav

Module 9: Testing Mean Differences

     The t tests and an associated graph.

     General comments & 1 regression with scatterplot and 1 oneway ANOVA w/graphs

     More detailed examination of ANOVA techniques.

Module 10: Regression

     Detailed examination of ordinary least squares (OLS) linear regression (1) (2) (3)

     An example of Canonical Correlation

     Syntax example of Simple Slopes Analysis -- testing moderation with OLS regression.

     Syntax example Testing Mediation w/ Aroian test and OLS regression (w/ this data).

     Categorical Regression with Optimal Scaling; and a Better Second Example

     Logistic Regression: Binary or Binomial and Multinomial

Module 11: Variable Reduction & Structure

     Traditional Principal Components Analysis

     Categorical Principal Components Analysis with optimal scaling

     Factor Analysis with Maximum Likelihood extraction

     Internal Consistency Analysis

     Correspondence Analysis: 2 variable example

     Exploration of Linear Mixed Models (i.e. Hierarchical Linear Modeling).

The DSA DIY Introduction to R short course
The DSA SAS short course


Contact Information

Jon Starkweather, PhD

Jonathan.Starkweather@unt.edu

940-565-4066

Richard Herrington, PhD

Richard.Herrington@unt.edu

940-565-2140

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Last updated: 2018.11.06 by Jon Starkweather.

Copyright 2012, 2013, 2014, 2015, 2016, 2017, 2018 by Jonathan D. Starkweather.

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