IBM SPSS Training

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IBM SPSS Training

Introduction to IBM SPSS

Gain a comprehensive overview of IBM SPSS, a leading statistical analysis software. Learn about its core features, capabilities, and how it supports various data analysis tasks.

Getting Started with SPSS

Learn how to install and set up IBM SPSS. Understand the basic interface, navigation, and initial configuration to start working with your data.

Data Entry and Management

Explore data entry and management in SPSS. Learn how to input data, define variables, and manage datasets efficiently.

Descriptive Statistics

Learn to perform descriptive statistical analysis using SPSS. Generate frequency tables, descriptive statistics, and visualizations to summarize your data.

Inferential Statistics

Delve into inferential statistics with SPSS. Understand hypothesis testing, t-tests, ANOVA, and chi-square tests to make inferences from your data.

Correlation and Regression Analysis

Explore correlation and regression analysis in SPSS. Learn to assess relationships between variables and build regression models to predict outcomes.

Advanced Statistical Techniques

Learn about advanced statistical techniques in SPSS. Study factor analysis, cluster analysis, and other methods to analyze complex datasets.

Data Visualization

Discover how to create and customize visualizations in SPSS. Use charts, graphs, and tables to present and interpret your data effectively.

Reporting and Output Management

Understand how to generate and manage reports in SPSS. Learn to customize output, export results, and create detailed reports for your analysis.

Best Practices and Troubleshooting

Explore best practices for using SPSS efficiently. Learn common troubleshooting techniques to address issues and optimize your use of the software.

Hands-On Labs and Projects

Apply your SPSS knowledge through hands-on labs and projects. Work on real-world scenarios to develop practical skills in data analysis and interpretation.

IBM SPSS Syllabus

1: Introduction to IBM SPSS

  • Overview of IBM SPSS software suite
    • Introduction to SPSS software
    • Understanding the role of SPSS in data analysis
  • Installation and Setup Instructions
    • System requirements
    • Installation steps
    • Initial setup and configuration
  • Introduction to SPSS Interface and Navigation
    • Main interface elements
    • Navigation tips and tricks

2: Data Management in SPSS

  • Importing Data from Different Sources
    • Excel files
    • CSV files
    • Databases
  • Data Manipulation and Cleaning Techniques
    • Handling missing values
    • Data transformations
    • Outlier detection and treatment
  • Variable and Value Labels
    • Creating and editing variable labels
    • Defining value labels
  • Merging and Appending Datasets
    • Combining datasets
    • Handling conflicts and duplicates

3: Descriptive Statistics

  • Measures of Central Tendency
    • Mean
    • Median
    • Mode
  • Measures of Dispersion
    • Range
    • Variance
    • Standard deviation
  • Frequency Distributions and Histograms
    • Creating frequency tables
    • Generating histograms
  • Summary Statistics and Data Visualization
    • Generating summary statistics
    • Data visualization techniques

4: Inferential Statistics

  • Introduction to Inferential Statistics
    • Concepts of inferential statistics
    • Importance in research
  • Hypothesis Testing Concepts
    • Formulating hypotheses
    • Types of errors
  • Parametric Tests
    • T-tests
    • ANOVA (Analysis of Variance)
  • Non-parametric Tests
    • Mann-Whitney U test
    • Kruskal-Wallis test

5: Bivariate Analysis

  • Correlation Analysis
    • Pearson correlation
    • Spearman correlation
  • Simple Linear Regression
    • Building the regression model
    • Interpreting results
  • Multiple Regression Analysis
    • Model building
    • Interpreting regression output
    • Diagnostics

6: Multivariate Analysis

  • Factor Analysis
    • Concepts of factor analysis
    • Interpreting factors
  • Cluster Analysis
    • Clustering techniques
    • Interpreting clusters
  • Discriminant Analysis
    • Concepts and applications
    • Interpreting results
  • Multivariate Analysis of Variance (MANOVA)
    • Concepts of MANOVA
    • Performing MANOVA

7: Logistic Regression

  • Introduction to Logistic Regression
    • Concepts and use cases
    • Model building and interpretation
  • Binary Logistic Regression
    • Building the model
    • Interpreting output
  • Multinomial Logistic Regression
    • Model building
    • Interpreting results

8: Advanced Topics

  • Advanced Data Management
    • Complex data manipulations
    • Advanced data transformations
  • Advanced Statistical Procedures
    • Advanced regression techniques
    • Complex survey data analysis
  • Advanced Data Visualization
    • Creating advanced charts and graphs
    • Interactive data visualizations
  • Integration with Other Tools
    • Exporting data to other software
    • Integrating SPSS with external tools and platforms
  • Automating Tasks and Scripting
    • Using SPSS syntax for automation
    • Writing and running scripts

Training

Basic Level Training

Duration : 1 Month

Advanced Level Training

Duration : 1 Month

Project Level Training

Duration : 1 Month

Total Training Period

Duration : 3 Months

Course Mode :

Available Online / Offline

Course Fees :

Please contact the office for details

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Note

100% Job Assurance Only
Daily online batches for employees
New course batches start every Monday
Download Syllabus