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SPSS Course Details

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SPSS Course Details

SPSS (Statistical Package for Social Sciences) training is available both online and offline. Here are some course recommendations:

SPSS Statistics Essential Training Course:

This course covers the basics of using IBM SPSS Statistics for data analysis. Students will learn about data reading, definition, modification, analysis, and presentation of results. They will also discover time-saving shortcuts. The course focuses on IBM SPSS Statistics Base, with an additional section on IBM SPSS Custom Tables.

The course includes topics such as data entry and analysis.

The SPSS statistics course provides a comprehensive understanding of statistical analysis tools and techniques.

Course Syllabus:

  1. Introduction
  • Overview of SPSS
  • Data analysis with SPSS: workflow, functions, commands
  • SPSS file management
  • Theoretical overview of statistical analysis tools
  1. Data Input and Cleaning
  • Variable definition
  • Manual and automated data input
  • Data cleaning
  • Data manipulation techniques
  1. Descriptive Data Analysis
  • Frequency analysis
  • Descriptive statistics
  • Data exploration
  • Crosstabs
  • Chart creation
  1. Statistical Tests
  • Mean analysis
  • T-test
  • One-way ANOVA
  • Non-parametric tests
  • Normality tests

Correlation and Regression techniques such as

  • Linear correlation and regression,
  • Multiple regression (linear) are covered.
  1. Multivariate analysis topics covered in this course include factor analysis and cluster analysis.

The course will cover the following modules:

Module 1: Introduction and Basics

  • Introduction
  • SPSS Environment
  • Opening a File in SPSS
  • Opening an Excel File
  • Reading Text Data

Module 2: Data and Variables

  • Creating New Variables
  • Recoding into Different Variables
  • Recoding into Same Variables
  • Summarisation of Data
  • Measurement Scales

Module 3: Analysing Data

  • Frequency Tables
  • Descriptive Statistics
  • Generating a Histogram
  • Generating Statistics
  • Building Graphs Easily
  • Cross Tables
  • Correlation Analysis
  • Linear Regression
  • Simple Linear Regression
  • Multiple Linear Regression

Module 4: Entering and Sorting Data

  • Select Cases
  • Sorting of Cases
  • Visual Binning
  • Dates and Times
  • Data Merge

Module 5: Testing

  • Hypothesis Testing
  • P-Value
  • Significance Levels
  • Confidence Intervals
  • Study Population and Sampling
  • Distributions
  • T-Tests
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