SPSS Combo (All 4 Courses) Course

Course Combo Refund Policy: Once payment is received, there are no refunds on instructor-led course bundles, due to a discount being given. However, you may reschedule any of the included classes if needed.

Certification Notes: Certification exams are administered by third party testing companies. Our courses prepare you for the certification exam, which is an additional fee paid to the testing provider. You must contact the corresponding testing provider to take a certification exam.

Introduction to SPSS (Days 1 & 2)

Overview
Windows
Designated Window versus Active Window
Status Bar
Dialog Boxes
Variable Names and Variable Labels in Dialog Box Lists
Resizing Dialog Boxes
Dialog Box Controls
Selecting Variables
Data Type, Measurement Level, and Variable List Icons
Getting Information about Variables in Dialog Boxes
Basic Steps in Data Analysis
Statistics Coach
Finding Out More

Getting Help
Getting Help on Output Terms

Data Files
Opening Data Files
To Open Data Files
Data File Types
Opening File Options
Reading Excel 95 or Later Files
Reading Older Excel Files & Other Spreadsheets
Reading dBase Files
Reading Stata Files
Reading Database Files
Text Wizard
Reading Dimensions Data
File Information
Saving Data Files
To Save Modified Data Files
Saving Data Files in External Formats
Saving Data Files in Excel Format
Saving Data Files in SAS Format
Saving Data Files in Stata Format
Saving Subsets of Variables
Exporting to a Database
Exporting to Dimensions
Protecting Original Data
Virtual Active File
Creating a Data Cache

Data Editor
Data View
Variable View
To Display or Define Variable Attributes
Variable Names
Variable Measurement Level
Variable Type
Variable Labels
Value Labels
Inserting Line Breaks in Labels
Missing Values
Column Width
Variable Alignment
Applying Variable Definition Attributes to Multiple Variables
Custom Variable Attributes
Customizing Variable View
Spell Checking Variable and Value Labels
Entering Data
To Enter Numeric Data
To Enter Non-Numeric Data
To Use Value Labels for Data Entry
Data Value Restrictions in the Data Editor
Editing Data
Replacing or Modifying Data Values
Cutting, Copying, and Pasting Data Values
Inserting New Cases
Inserting New Variables
To Change Data Type
Finding Cases or Variables
Finding and Replacing Data and Attribute Values
Case Selection Status in the Data Editor
Data Editor Display Options
Data Editor Printing
To Print Data Editor Contents

Working with Multiple Data Sources
Basic Handling of Multiple Data Sources
Working with Multiple Datasets in Command Syntax
Copying and Pasting Information between Datasets
Renaming Datasets
Suppressing Multiple Datasets

Working with Output
Viewer
Showing and Hiding Results
Moving, Deleting, and Copying Output
Changing Initial Alignment
Changing Alignment of Output Items
Viewer Outline
Adding Items to the Viewer
Finding and Replacing Information in the Viewer
Copying Output into Other Applications
To Copy and Paste Output Items into Another Application
Export Output
HTML, Word/RTF, and Excel Options
PowerPoint Options
PDF Options
Text Options
Options for Exporting Charts
Viewer Printing
To Print Output and Charts
Print Preview
Page Attributes: Headers and Footers
Page Attributes: Options
Saving Output
To Save a Viewer Document

Working with Command Syntax
Syntax Rules
Pasting Syntax from Dialog Boxes
To Paste Syntax from Dialog Boxes
Copying Syntax from the Output Log
To Copy Syntax from the Output Log
To Run Command Syntax
Unicode Syntax Files
Multiple Execute Commands

Crosstabs
Crosstabs Layers
Crosstabs Cluttered Bar Charts
Crosstabs Statistics
Crosstabs Cell Display
Crosstabs Table Format

Overview of the Chart Facility
Building and Editing a Chart
Building Charts
Editing Charts
Chart Definition Options
Adding and Editing Titles and Footnotes
Setting General Options

 

Data Management & Manipulation with SPSS (Days 3 & 4)

Choices in Running SPSS
• Different Modes of Running SPSS
• Menus and Dialogs
• SPSS Syntax Editor and SPSS Commands
• SPSS Production Mode Facility
• When to Use the Different Modes
• Summary Exercises

Further Data Transformation Features
• Introduction
• Automatic Recode
• Counting Values Across Variables
• If Conditions
• Do If Else If Logic
• Conditional Count Transformation
• Summary Exercises

Computing Numeric Variables
• Introduction
• Using Functions In SPSS
• The Any and Range Functions
• Missing Functions
• Useful System Variables
• Summary Exercises

Computing Date, Time, And String Variables
• Introduction
• Working with Dates and Times
• Converting String Variables to Date Variables
• String Transformations
• Summary Exercises

Helpful Data Management Features
• Introduction
• Identifying Duplicate Cases
• Custom Variable Attributes
• Variable Sets
• Saving Selected Variables
• Displaying SPSS Data File Properties
• Directing Output to A Different Viewer Window
• Summary Exercises

Aggregating Data
• Introduction
• Data Aggregation
• Aggregate the Country Data to A Separate Region File
• Aggregate Region Variables to The Country File
• Summary Exercises

Merging Files – Adding Cases
• Adding Cases In SPSS
• Checking the SPSS Data File
• Reading the Dbase File
• Adding the Files
• Exploring the Combined File
• Testing Mean Differences – T Test
• Appendix: Adding Cases from More Than Two Files
• Summary Exercises

Merging Files – Adding Variables
• Introduction
• Considerations in File Merging
• A One-To-One Match
• Measuring Change
• Reporting the Changes
• A One-To-Many Match
• A One-To-Many Match Example
• Appendix: Adding Variables from More Than Two Files
• Summary Exercises

Editing Charts and Pivot Tables
• Introduction
• Chart Templates
• Setting A Default Chart Template
• Editing Pivot Tables
• Rules for Editing Pivot Tables
• Table Properties
• Editing Cell Properties
• Showing and Hiding Cells
• Creating Category Groups
• Rotating Labels
• Summary Exercises

Deployment of SPSS Results
• Introduction
• Three Types of SPSS Output
• ActiveX and SPSS
• Moving Pivot Table Output to Other Applications
• Pasting Pivot Tables into Spreadsheets
• Pasting Standard Graphics From SPSS
• Moving Text Output from SPSS To Word Processors
• Exporting SPSS Output
• SPSS Output Management System
• Summary Exercises

Controlling the SPSS Environment
• SPSS Options
• General Tab
• Viewer Tab
• Draft Viewer Tab
• Output Labels Tab
• Charts Tab
• Pivot Tables Tab
• Data Tab
• Scripts Tab
• Using the Set Command

 

Introduction to Statistical Analysis using SPSS (Days 5 & 6)

Introduction to Statistical Analysis

Principles of Research Design and Process

Data Cleaning and Preparation: Using the Add-on Data Preparation Module

Describing Categorical Data

Summarizing Continuous Data

Measures of Central Tendency and Dispersion

Checking the form of distribution

Probability and inferential statistics

Comparing Categorical Variables

Measures of Association

Mean Differences between Groups: T Test

Bivariate plots and correlations

Introduction to Regression

Appendix A: Mean differences between Groups: One-Factor ANOVA

Appendix B: Introduction to Multiple Regression

 

Advanced Statistical Analysis using SPSS (Days 7 & 8)

Introduction and Overview
•Goals of the Course
•Taxonomy of Methods
•General Approach
•Summary

Discriminant Analysis
•How Does Discriminant Analysis Work?
•The Elements of Discriminant Analysis
•The Discriminant Model
•How Cases are Classified
•Assumptions of Discriminant Analysis
•A Two-Group Discriminant Example
•Checking Variance Assumptions
•Running a Discriminant Analysis
•The Discriminant Coefficients
•Classification Statistics 2- 18 Prediction
•The Assumption of Equal Covariance
•Modifying the List of Predictors
•Casewise Statistics and Outliers
•Adjusting Prior Probabilities
•Validating the Discriminant Model
•Stepwise Model Selection
•Three-Group Discriminant Analysis
•Summary

Binary Logistic Regression
•How Does Logistic Regression Work?
•The Logistic Equation
•The Elements of Logistic Regression
•Assumptions of Logistic Regression
•A First Example of Logistic Regression
•Interpreting Logistic Regression Coefficients
•Making Predictions
•The Accuracy of Prediction
•Estimated Probabilities
•Checking Classifications
•Residual Analysis
•Stepwise Logistic Regression
•Summary
•Appendix: Comparison to Discriminant Analysis

Multinomial Logistic Regression
•Multinomial Logistic Model
•Assumptions of Multinomial Logistic Regression
•A Multinomial Logistic Analysis: Predicting Credit Risk
•Interpreting Coefficients
•Classification Table
•Making Predictions
•Appendix: Multinomial Logistic with a Two-Category Outcome

Survival Analysis (Kaplan-Meier)
•What is Survival Analysis
•Concepts
•Censoring
•What to Look for in Survival Analysis
•Survival Procedures in SPSS
•An Example: Kaplan-Meier
•Results
•Extensions
•Summary

Cluster Analysis
•How Does Cluster Analysis Work?
•Types of Data Used for Clustering
•What to Look at When Clustering
•Methods
•Distance and Standardization
•Overall Recommendations
•Example I: Hierarchical Cluster Analysis
•Cluster Results
•Obtaining Mean Profiles of Clusters
•Relating Clusters to Other Variables
•Summary of First Cluster Example
•Example II: K-Means Clustering
•Running K-Means Clustering
•Summary

Factor Analysis
•Uses of Factor Analysis
•What to Look for When Running Factor Analysis
•Principles
•The Idea of a Principal Component
•Factor Analysis Versus Principal Components
•Number of Factors
•Rotation
•Factor Scores & Sample Size
•Methods
•An Example: 1988 Olympic Decathlon Scores
•Looking at Correlations
•Principal Components Analysis with an Orthogonal Rotation
•Principal Axis Factoring with an Oblique Rotation
•Summary

Loglinear Analysis
•What are Loglinear Models
•Relations Among Loglinear, Logit Models and Logistic Regression
•What to Look for in Loglinear and Logit Analysis
•Assumptions
•Procedures in SPSS that Run Loglinear or Logit Analysis
•Example: Analysis of Location Preference (Model Selection)
•Running the Analysis
•Significance Tests
•Coefficient Interpretation
•Summary
•Appendix: Logit Analysis with Specific Model (Genlog)
•Results

Multivariate Analysis of Variance
•Why Perform MANOVA
•Assumptions of MANOVA
•What to Look for in MANOVA
•SPSS Version 7 Differences
•An Example: Memory Influences
•Examining the Output
•Post Hoc Tests
•Summary
•Appendix: Post Hoc Testing of Means

Repeated measures Analysis of Variance
•Why do a Repeated Measures Study
•The Logic of Repeated Measures
•Assumptions
•Example: One Factor Drug Study
•Examining Results
•Further Analysis
•Planned Comparisons
•Summary
•Appendix: Ad Viewing with Pre-Post Brand Ratings
•Examining Results
•Tests of Assumptions
•Profile Plots
•Extensions