Question

Given here is a set of Y-X data points, using spread sheets least square fit

the given data for a straight line Y = mX + c case.

Mass (Y) 341.59 338.92 340.39 338.43 337.57

W (X) 0.01 0.02 0.03 0.04 0.05

The expressions for ‘m’ and ‘c’ are as follows.



m = (n∑X*Y - ∑X * ∑Y)/[n∑X2 – ((∑X)2

)]

c = (∑X2 ∑Y - ∑X * ∑X*Y)/[n∑X2 – ((∑X)2

)]

From the least square fitting of the data calculate the parameters ‘m’ and

‘c’ hence the equation Y = mX + c

Make a plot of original ‘X’ & ‘Y’ data showing the deviation of points from

straight line. Fit the ‘TRENDLINE’ equation & compare the coefficients ‘m’

& ‘c’ with those obtained above.
​

Answer 1

Answer:

Explanation:

Given here is a set of Y-X data points, using spread sheets least square fit

the given data for a straight line Y = mX + c case.

Mass (Y) 341.59 338.92 340.39 338.43 337.57

W (X) 0.01 0.02 0.03 0.04 0.05

The expressions for ‘m’ and ‘c’ are as follows.

m = (n∑X*Y - ∑X * ∑Y)/[n∑X2 – ((∑X)2

)]

c = (∑X2 ∑Y - ∑X * ∑X*Y)/[n∑X2 – ((∑X)2

)]

From the least square fitting of the data calculate the parameters ‘m’ and

‘c’ hence the equation Y = mX + c

Make a plot of original ‘X’ & ‘Y’ data showing the deviation of points from

straight line. Fit the ‘TRENDLINE’ equation & compare the coefficients ‘m’

& ‘c’ with those obtained above.

​