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Course Introduction to IBM SPSS Statistics & Statistical Analysis

Course outline

3 days
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Duration

3 days

Course Overview

This customized 3-day course logically guides attendees through the fundamentals of using IBM SPSS Statistics as well as to perform multivariate statistical analyses necessary for their research needs. 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 statistical modeling, they will gain that vital experience and knowledge that will transform them from SPSS novices to productive data analysts.

Who is the course designed for?

This course is designed for those people with little or no experience of IBM SPSS Statistics. Attendees should have a basic familiarity with operating in the Windows environment and should be acquainted with statistical terms. Exposure in biostatistics is recommended.

Course Contents

Following an overview of the main features of IBM SPSS Statistics, and an introduction to multivariate analyses, the course will proceed logically through the following topics: -

Day 1

1.0 Introducing IBM SPSS Statistics

  • Introduction to IBM SPSS Statistics
  • Basic Steps in Data Analysis
  • Running a Basic Analysis

2.0 Data Access

  • Reading SPSS Files
  • Reading Microsoft Excel
  • Reading a Text File
  • Reading Data From Database

3.0 Working with Data Editor

  • Enter Data in the Data Editor
  • Enter Data Values in the Data Editor
  • Spell Check
  • Inserting and Deleting Variables & Cases
  • View Values for Multiple Variables: Split Screen
  • Working with Multiple Datasets
  • Copy Data Properties Feature

4.0 Summarizing Individual Variables

  • Central Tendency & Dispersion
  • Summarizing Categorical Variables
  • Summarizing Scale Variables
  • Summarizing Scale Variables using Descriptive

5.0 Modifying Data Values: Recode and Compute

  • Visual Binning
  • Recode into Different Variables
  • Automatic Recode of Variables
  • Computing Variables
  • Computing with Functions
  • Conditional Compute

6.0 Reporting the Results: Graph & Tables

  • Building Graph
  • Customizing Graph
  • Table with Mean
  • Custom Table
  • Customizing Pivot Table
  • Pasting Results to Other Applications
  • Exporting Results to Other Applications

Day 2

7.0 Regression Analysis

  • Data Requirement
  • Scatter Plots
  • Correlations
  • Obtaining the Regression Model
  • Interpretation of the Regression Coefficients
  • Testing the Model Fit
  • Explained & Unexplained Variations
  • Diagnostic Tests
  • Prediction

Day 3

8.0 Survival Analysis

  • The Life Table
  • Survival and Hazard Functions
  • Kaplan Meyer Analysis
  • Test Between Groups
  • Cox Regression Analysis
  • Interpretation of the Coefficients
  • Testing Assumptions
  • Extended Cox Regression Analysis
  • Prediction

Programme scope, delivery arrangements and suitability are confirmed during enquiry.