In: Accounting
Answer : 3 (a)
(i) Calculation of regression coefficients ? and ? Using least-squares method :
Store | X | Y | XY | ||
1 | 5 | 8 | 25 | 64 | 40 |
2 | 7 | 12 | 49 | 144 | 84 |
3 | 2 | 6 | 4 | 36 | 12 |
4 | 8 | 14 | 64 | 196 | 112 |
5 | 4 | 8 | 16 | 64 | 32 |
6 | 3 | 7 | 9 | 49 | 21 |
7 | 2 | 9 | 4 | 81 | 18 |
8 | 4 | 10 | 16 | 100 | 40 |
9 | 5 | 12 | 25 | 144 | 60 |
10 | 3 | 8 | 9 | 64 | 24 |
Total | 43 | 94 | 221 | 942 | 443 |
From above,
ΣX = 43
ΣY = 94
ΣXY = 443
a = 4.778
b = 1.075
So, Regression coefficient a = 4.778
Regression coefficient b = 1.075
(ii)
Estimated Equation Is Y = 4.778 + 1.075X
If there are 9000 Customers, then monthly sales will be
X = 9
Y = 4.778 + 1.075 x 9
Y = 14.453
So, If there are 9000 Customers, then monthly sales will be 14,453
(iii) Calculation of coefficient of determination
Coefficient of Correlation =
= 0.845
Coefficient of determination = 0.7140 = 71.40%
Coefficient of determination determines the percentage of variation accounted by factor under consideration.
So, In above case this means that 71.40% change in Monthly Sales has been accounted by Number of Customers.
(iv) The Value of the extent of relationship between annual sales and number of customers is represented by the Coefficient of correlation and it is 0.845
Interpretion
Because Coefficient of correlation is Positive and it is near to 1, We can conclude that there is positive relationship between annual sales and number of customers and this relationship is strong.