Significance and Limitations
Significance of Sum of Squares
The sum of squares formula can be used for various purposes and has great significance in real life such as:
- It can be used to find the variability of data points from the mean value.
- It helps the investors to make a good decision regarding investment by checking the variance of the stock.
- It can also help to compare the stock price of two different companies.
Limitations of Sum of Squares
The sum of squares has the following limitations:
- A higher dataset makes it very difficult to make decisions in real life as the graph of the data is more spread out.
- An investor may need data of many years to make good decisions but this huge data becomes very difficult to handle.
Residual Sum of Squares
Residual Sum of Squares is one of the types of sum of squares in regression which is used to measure the dispersion of the data points. The sum of squares can also be used to calculate the variance in the values of assets in the case of accounting. If the value of the sum of squares is higher, it represents a higher variance from the mean value and vice versa. The sum of squares is generally of 3 types i.e. Total Sum of Squares, Regressive or Regression Sum of Squares, and Residual Sum of Squares. In this article, we will study majorly the types of Residual Sum of Squares. Other than this we will also discuss both other types in bried as well.