Duration
3 days
Course Description
This comprehensive 3-days course logically guides attendees through the fundamentals of using IBM SPSS Statistics as well as to provide basic statistics knowledge necessary for their research needs. 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 IBM SPSS Statistics so as to get the most from their data. Through a series of “hands-on” sessions and exposure on the basic statistics concepts, they will gain that vital experience and knowledge that will transform them from SPSS novices to productive data analysts with basic understanding in statistics theory.
Audience
This course is designed for those people with little or no experience of IBM SPSS Statistics and with very minimal or no knowledge of statistics. Attendees should have a basic familiarity with operating in the Windows environment and should be acquainted with statistical terms.
Course Outline
Following an overview of the main features of IBM SPSS Statistics, and an introduction to essential statistical terminology, the course will proceed logically through the following topics: -
1.0 The Modern Statistics
- Types of Research Design
- Types of Data
- Levels of Measurement
- Preparing the Data for Analysis
2.0 Introducing IBM SPSS Statistics
- Introduction to IBM SPSS Statistics
- Basic Steps of Data Analysis
- Use Variable View and Variable Properties
- Data Entry Using IBM SPSS Statistics
- Running a Basic Analysis
3.0 Reading Data
Introduction
- The File Menu
- Reading Excel and Other Spreadsheet Files
- Reading Data from Database
- Reading a Text File
- Reading a Delimited Text File
4.0 Working with Data Editor
- Steps to Use Define Variable Properties
- Spell Checker
- Inserting and Deleting Variables and Cases
- View Values for Multiple Variables: Split Screen
- Working with Multiple Datasets
- Multiple Datasets Copy and Paste
- Copy Data Properties Feature
5.0 Central Tendency & Dispersion
- Measures Of Central Tendency
- Measures Of Dispersion
6.0 Summarizing Individual Variables and Creating Charts
- Level of Measurement
- Summarizing Nominal Variables
- Summarizing Ordinal Variables
- Summarizing Scale Variables
- Descriptive for Scale Variables
- Creating Graphs Using Chart Builder
- Customizing Charts
7.0 Modifying Data Values: Recode and Compute
Introduction
- Visual Binning
- Recode into Different Variables
- Automatic Recode of Variables
- Computing Variables
- Computing with Functions
- Conditional Compute
8.0 The Normal Distribution and Application
- The Nature of Probability
- Histogram With A Normal Curve
- Skewness & Kurtosis
- Using Explore To Check For Normality
- Assessing Normality Using All Available Evidence
- Transforming Data
9.0 The Fundamental of Hypothesis Testing
- Hypothesis Testing
- Type I and Type II Errors
10.0 Application of T-Tests
- Exploring The Relationship
- Graphing The Relationship
- The Independent Groups T-Test
- A Non-Parametric Equivalent To The T-Test
- Other: The Paired T-Test
11.0 Selecting Cases
- Data Selection
- Selecting Cases Using If Condition
- Deleting Unselected Cases
- Split File Processing
12.0 Testing Relationships Between Categorical Variables
- What Is Meant By "Testing Relationships Between Categorical Variables”?
- Crosstabulation Tables
- Requesting A Clustered Bar Chart
- Hypothesis Testing: Are The Two Variables Related?
- The Chi-Square Statistic
- Interpreting The Chi-Square Output
- Sample Size
- Two-By-Two Crosstabs
- Contribution From Each Cell
- Adding Control Variables
- Customizing Pivot Tables
13.0 Syntax Basics
Introduction
- Syntax Compared to Commands from Menus
- Pasting From Dialogs to Generate Syntax
- Syntax Editor
- Editing Syntax and Running Edited Syntax
- Syntax Errors
Appendix A: Mean Differences Between Groups: One-Factor ANOVA
- Extending the Logic Beyond Two Groups
- Exploring the Data
- One-Factor ANOVA
- Graphing the Mean Differences
This is a version-specific reference outline. Confirm the current syllabus and delivery arrangements with EIEIO.