SPSS Tutorial for Data Analysis
A comprehensive guide to data analysis using SPSS with a real-world dataset
Overview
This project involves creating a detailed tutorial on data analysis using SPSS, applied to the 'Machine Predictive Maintenance Classification' dataset from Kaggle. It covers descriptive statistics, inferential statistics, regression analysis, and more, serving as an educational resource for beginners and intermediate learners.
Key Features
- Introduction to SPSS and its interface
- Data preparation and management
- Descriptive statistics: measures, distributions, and graphs
- Inferential statistics: t-tests, ANOVA, chi-square
- Regression analysis: linear and logistic
Development Process
The team collaborated to design the tutorial structure, implement analyses in SPSS using the dataset, and document each step with explanations and examples.
Project Details
- Date
- 2023
- Category
- Data Analytics
- Team
- Mohamed Boukri Nouhaila Bouhddi Yassine Zegroud
- Client
- Academic Project
Technologies Used
Project Links
Challenges and Solutions
Balancing Depth and Accessibility
Ensuring the tutorial is comprehensive yet understandable for users with varying statistical knowledge.
Solution: Incorporated foundational explanations and progressive examples.
Results and Impact
The tutorial provides a practical resource for learning SPSS-based data analysis, with real-world applications from the predictive maintenance dataset.