SPSS / STATISTICA

The "SPSS / STATISTICA for Data Science" training is designed to equip participants with practical skills in using SPSS and STATISTICA for data analysis, statistical modeling, and decision-making.

Over four days, attendees will learn how to manipulate data, perform statistical tests, visualize insights, and apply advanced analytics techniques essential for data science.

This hands-on workshop will bridge the gap between statistical tools and real-world applications.

Workshop Overview

Learning Outcomes

• Navigate SPSS / STATISTICA interfaces for efficient data analysis.

• Perform descriptive and inferential statistics.

• Conduct hypothesis testing and statistical significance analysis.

• Apply regression models (linear, logistic, multiple).

• Use ANOVA, MANOVA, and correlation analysis.

• Generate visualizations and interpret results effectively.

• Apply predictive analytics and "supervised" machine learning solutions.

• Explore data with "unsupervised" machine learning.

Detailed Course Schedule

• Day 1:

  • Data Visualization and Statistical Analysis

• Day 2:

  • Statistical Analysis: t-test, Chi-Squares, and ANOVA

• Day 3:

  • Multiple Regressions, Discriminant Analysis, Decision Trees, Naive Bayes, etc.

• Day 4:

  • Dimension Reducibility: PCA, t-SNE

  • Clustering: Agglomerative, K-Means, etc.

• Exploring SPSS and STATISTICA for data analysis.

• Understanding core statistical concepts for data-driven decision-making.

• Data cleaning, transformation, and visualization techniques.

• Applying statistical models for business and research insights.

• Hands-on practice with real datasets to reinforce learning.

• Leveraging automation tools for efficient workflows.

• Interpreting results to make data-driven conclusions.

What will it be about?