This repository contains a project where we applied simple linear regression to predict the charges for individuals based on their age. Specifically, we focus on predicting the charges for a 70-year-old person.

The goal of this project is to use a simple linear regression model to estimate the charges incurred by individuals based on their age. By fitting a linear model to the data, we can make predictions for charges at specific ages, such as 70 years old.

The analysis involves the following steps:

Data Preprocessing: Preparing the data for model training. Exploratory Data Analysis: Visualizing the relationship between age and charges. Simple Linear Regression: Fitting a linear regression model to predict charges based on age. Prediction: Using the model to predict the charges for a 70-year-old person.

The key findings were:

Linear Relationship: The analysis confirms a linear relationship between age and charges. Model Coefficients: The regression model provides coefficients that quantify the relationship. Prediction for 70-Year-Old: The predicted charges for a 70-year-old individual are calculated using the model.

Model Coefficients:

Intercept: 𝛽 0 ​

Slope (Age coefficient): 𝛽 1 ​

Prediction for a 70-Year-Old:

Using the model Charges= 𝛽 0 + 𝛽 1 × Age Charges=β 0 ​ +β 1 ​ ×Age, the predicted charges for a 70-year-old person are calculated.