SPSS Introduction/Intermediate
Duration: 2 Days
Overview:
Click here for printer
friendly version of outline
Get up to speed in SPSS quickly and easily on Aspect Training’s Introduction/Intermediate
two-day course. Learn how to import data into SPSS and set it up ready for further
analysis. You will perform basic statistical analyses, data checking and create
simple tables and charts. This course will focus on getting you comfortable with
using SPSS for Windows and ready to explore further data analysis possibilities.
Aspect Training’s comprehensive 2-days course logically guides’ attendees through
the fundamentals of using SPSS for Windows. The course is structured so as
to provide effective training in all the 4 stages of a typical data analysis process
– data definition and input, data modification, data analysis and data presentation.
Attendees will learn to efficiently utilize the power and flexibility of SPSS for
Windows so as to get the most from their data. Through a series of “hands-on”
sessions, they will gain that vital experience that will transform them from SPSS
novices to productive data analysts.
Prerequisites:
This two-day course is aimed at new users of SPSS.
Delegates should have:
Experience with running software in a Windows environment
No prior SPSS knowledge is required.
Course Topics:
Introduction
Opening a Data File
Running an Analysis
Viewing Results
Creating Charts
Reading Data
Basic Structure of SPSS Statistics Data Files
Reading SPSS Statistics Data Files
Reading Data from Spreadsheets
Reading Data from a Database
Reading Data from a Text File
Using the Data Editor
Entering Numeric Data
Entering String Data
Defining Data
Adding Variable Labels
Changing Variable Type and Format
Adding Value Labels for Numeric Variables
Adding Value Labels for String Variables
Using Value Labels for Data Entry
Handling Missing Data
Missing Values for a Numeric Variable
Missing Values for a String Variable
Copying and Pasting Variable Attributes
Defining Variable Properties for Categorical Variables
Working with Multiple Data Sources
Basic Handling of Multiple Data Sources
Copying and Pasting Information between Datasets
Renaming Datasets
Suppressing Multiple Datasets
Examining Summary Statistics for Individual Variables
Level of Measurement
Summary Measures for Categorical Data
Charts for Categorical Data
Summary Measures for Scale Variables
Histograms for Scale Variables
Creating and Editing Charts
Chart Creation Basics
Using the Chart Builder Gallery
Defining Variables and Statistics
Adding Text
Creating the Chart
Chart Editing Basics
Selecting Chart Elements
Using the Properties Window
Changing Bar Colours
Formatting Numbers in Tick Labels
Editing Text
Displaying Data Value Labels
Using Templates
Defining Chart Options
Working with Output
Using the Viewer
Using the Pivot Table Editor
Accessing Output Definitions
Pivoting Tables
Creating and Displaying Layers
Editing Tables
Hiding Rows and Columns
Changing Data Display Formats
TableLooks
Using Predefined Formats
Customizing TableLook Styles
Changing the Default Table Formats
Customizing the Initial Display Settings
Displaying Variable and Value Labels
Using Results in Other Applications
Pasting Results as Word Tables
Pasting Results as Text
Exporting Results to Microsoft Word, PowerPoint, and Excel Files
Exporting Results to PDF
Exporting Results to HTML
Modifying Data Values
Creating a Categorical Variable from a Scale Variable
Computing New Variables
Using Functions in Expressions
Pasting a Function into an Expression
Editing a Function in an Expression
Using Conditional Expressions
Working with Dates and Times
Calculating the Length of Time between Two Dates
Adding a Duration to a Date
Sorting and Selecting Data
Sorting Data
Split-File Processing
Sorting Cases for Split-File Processing
Turning Split-File Processing On and Off
Selecting Subsets of Cases
Selecting Cases Based on Conditional Expressions
Selecting a Random Sample
Selecting a Time Range or Case Range
Treatment of Unselected Cases
Case Selection Status
Additional Statistical Procedures
Summarizing Data
Explore
More about Summarizing Data
Comparing Means
Means
Paired-Samples T Test
More about Comparing Means
ANOVA Models
Univariate Analysis of Variance
Correlating Variables
Bivariate Correlations
Partial Correlations
Regression Analysis
Linear Regression
Nonparametric Tests
Chi-Square