The objective of this project was to find out the impact of Years of work experience on salary. The dataset had two columns, years of experience and salary. The aim was to find out the linear relationship between years of experience and salary using the machine learning model of linear regression. Since the variables were two, this project is classified as simple linear regression.
Based on the results, the regression line from the scatterplot highlighted a positive relationship exists between years of experience and salary. The coefficients were situated along the regression line indicating a linear relationship or homoscedasticity (in statistical terms). To further evaluate the accuracy of this Machine learning model, the Mean Squared Error of 2.5 shows that the model has fewer errors in predicting the actual data. Therefore, there is the confidence that the prediction model is representative of the actual data and is therefore valid and reliable.