The document discusses the least squares method, which is a statistical technique for finding the best-fitting linear regression line for a set of data points by minimizing the sum of the squared residuals, or offsets of the data points from the line. It provides the formulas for calculating the slope (b) and y-intercept (a) of the regression line, and applies the method to fit trend lines to sample sales data for TVs and air conditioners from 2007 to 2012, predicting future sales for 2015.

1. THE LEAST SQUARE METHOD

2. The least square method
The least square method is the process of finding the
best-fitting curve or line of best fit for a set of data
points by reducing the sum of the squares of the
offsets (residual part) of the points from the curve.

4. Least Square Method Definition
The least-squares method is a crucial statistical
method that is practised to find a regression line or a
best-fit line for the given pattern.

5. a= Y / N
b= XY / X2

7. Year 2007-08 2008-09 2009-10 2010-11
Sales of
TV in lakh
12 18 20 23
2011-12
27

9. Fit a straight line trend by Least
Square Method
Year 2007 2008 2009 2010 2011 2012
Sales of
AC
10 13 16 21 24 30

11. What will be Predicted sales for
2015