Linear regression uses summation of least squares to find the best fit. Why? I fully understand that we do not want to use actual residuals, otherwise, positive and negative numbers may cancel out each other. Then, why don't we use absolute values? Sorry if this sounds like a duplicate question. I did see many explanations but did not see an easy-to-understand answer. For example, some said that squares made calculation easier. How come?

Your insight is highly appreciated!