📊 Statistical Projects

This repository contains exercises and projects from my university courses, focusing on statistical software, statistics, and probability.
The projects are implemented using Jupyter Notebooks and SPSS, covering various statistical analysis techniques.

📁 Project Structure

The repository is organized into two main directories:

• Statistical Software

1. How to draw different statistical plots in Python
2. t-tests with examples in Python

• Statistics and Probability

Description of the first project: load the attached mtcars dataset into SPSS and present the following in a report and upload it in pdf format.

1. data loading the dataset in SPSS
2. Provide appropriate descriptive statistics tables for all variables.
3. Provide appropriate charts for all variables
4. Coding continuous variables to obtain a frequency table
5. Interpretation of items 2, 3, and 4 should be provided after the output of each section.

Description of the second project: In both Dataset1 and Dataset2:

1. Determine the number of variables and observations in each dataset.
2. Identify which variables are quantitative and which are qualitative.
3. Calculate the appropriate statistics for each variable.
4. Create suitable charts for each variable.
5. In Dataset1, compare the income distribution between male and female categories. Check for normality if necessary.
6. In Dataset1, compare the income mean to 65.
7. In Dataset2, compare the 'Before' and 'After' columns using the appropriate test. Check for normality if necessary.

🧰 Technologies & Tools Used

• Languages & Platforms:
  • Python
  • SPSS (IBM Statistical Package for the Social Sciences)