IBM SPSS - SPSS Certification

Introduction

This SPSS Training Course teaches candidates the fundamentals of using SPSS. SPSS is the data management software package produced by IBM and makes statistical data analysis straightforward.

It functionality ranges from simple plots and charts, through to much more sophisticated statistical tests.

Although very broadly applicable, SPSS is very well suited to analysing survey data.

This course includes hands-on exercises in a workshop environment.

Upon completion of this course, candidates will be able to perform basic statistical analyses, data checking and create simple tables and charts.

This course allows individuals to work independently with SPSS on their own data and provides a solid foundation for more advanced data analysis work.

Pre-Requisites

• Basic experience with the Windows operating system and some understanding of statistical analysis is needed, prior to attending this course.

Who Should Attend

• Recommended for those who require knowledge on SPSS.

Course Content

General Concepts

• The Data Analysis Process
• Surveys vs Experiments
• SPSS Window Types: Data, Output, Syntax
• SPSS File Types: Data, Output

• The “case” concept
• Choosing the right Measure
• Creating Variables and choosing the right type
• Variable and Value Labels
• Calculating new variables
• Variable Recode
• Importing data from other programs (i.e. Excel)

• Frequency Tables
• Descriptive Statistics
• Crosstabulations
• Charts: Frequency, Cluster, Stacked, Value Bar Charts
• Simple Statistics on Groups: Computing Mean, Standard Deviation

• Modifying Output Tables and Charts
• Using Chart Templates
• Using Table “Looks”
• Including output in other applications (i.e. Word)

• Getting data from other sources
• Dealing with missing values
• Selecting Cases
• Using Sets
• The “Visual Bander”
• Splitting files
• Aggregated files
• Dealing with multiple response questions
• Data restructuring
• Working with dates, times and durations
• Merging files

• Introduction to statistical analysis
• Choosing the right Analysis
• Describing categorical data
• Exploratory data analysis: scale data
• Probability and inferential statistics
• Comparing categorical variables
• Mean differences between group: T-Tests
• Bivariate plots and correlations: scale variables
• A look into many of the Statistical tests
• Introduction to regression
• Data checking
• Introduction to multiple regression

• Introduction to SPSS Syntax
• The concept of significance
• Using chi-square