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https://github.com/fabianacampanari/statisticalmeasures

Statistical Measures in Python - Age and Salary Analysis
https://github.com/fabianacampanari/statisticalmeasures

hypothesis-testing math numpy pandas-python scipy-stats statisctics

Last synced: 24 days ago
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Statistical Measures in Python - Age and Salary Analysis

Host: GitHub
URL: https://github.com/fabianacampanari/statisticalmeasures
Owner: FabianaCampanari
License: mit
Created: 2024-10-16T20:13:06.000Z (about 1 month ago)
Default Branch: main
Last Pushed: 2024-10-20T17:34:36.000Z (27 days ago)
Last Synced: 2024-10-21T00:33:27.291Z (26 days ago)
Topics: hypothesis-testing, math, numpy, pandas-python, scipy-stats, statisctics
Language: Jupyter Notebook
Homepage: https://github.com/FabianaCampanari/statisticalMeasures-python-
Size: 231 KB
Stars: 1
Watchers: 1
Forks: 0
Open Issues: 0
Metadata Files:
- Readme: README.md
- Funding: .github/FUNDING.yml
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
- Citation: CITATION.cff

Awesome Lists containing this project

README

![2129d7ad-6afd-4166-9bf1-a4f9c3b9e5cc](https://github.com/user-attachments/assets/faf3e0a3-3610-4c0b-99bb-afb7a765f28d)

Statistical Measures in Python - Age and Salary Analysis

This repository contains a Python script that performs various statistical analyses on a dataset of employees. The script calculates descriptive statistics for the variables age (idade) and salary (salario) across the dataset as a whole and grouped by certain categories such as region (reg_proc) and education level (grau_instrucao).

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[![Sponsor FabianaCampanari ](https://img.shields.io/badge/Sponsor-FabianaCampanari-brightgreen?logo=GitHub)](https://github.com/sponsors/FabianaCampanari)

## Features:

Descriptive statistics: Mean, Median, Mode, Variance, Standard Deviation, Coefficient of Variation (CV), and Amplitude (Range).
Grouped analysis: The same statistics calculated by grouping data based on region and education level.
Designed for students: Easy-to-follow code with comments and explanations for each step.

## Dataset:

The dataset used in this analysis contains employee details, including their age, salary, region of origin (reg_proc), and education level (grau_instrucao).
[Click here to get the Dataset](https://github.com/FabianaCampanari/statisticalMeasures-python-/tree/a9e92b1cbce36fa5f26edeadef937981012f0a98/Dataset)

## Getting Started:

### To run this script, ensure you have the following:

- Python 3 installed.

- Necessary libraries (pandas) installed.

- An Excel file containing the dataset in the appropriate format.

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