Introduction:

This Jupyter Notebook contains a comprehensive descriptive statistical analysis of a dataset. Descriptive statistics are an integral part of the Exploratory Data Analysis (EDA) process, helping data analysts to compare variables, understand data distribution, identify outliers, and perform calculations for making predictions.

Getting Started:

1. Clone or download this repository to your local machine.
2. Ensure you have Jupyter Notebook installed. If not, you can install it using Anaconda or pip.
3. Open the Jupyter Notebook file (Descriptive_Statistical_Analysis.ipynb) in your Jupyter Notebook environment.
4. Execute the code cells step by step to replicate the analysis or modify it for your specific dataset.
5. import dataset

Aknowledgemen: Data provided by Google Learning under fair use.

Requirements

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from scipy import stats
import statsmodels.api as sm