Showing posts with label Solution Of Assignment No.2 (Course STA301) Fall 2012. Show all posts
Showing posts with label Solution Of Assignment No.2 (Course STA301) Fall 2012. Show all posts

Monday, 19 November 2012

Solution Of Assignment No.2 (Course STA301) Fall 2012


Solution Of Assignment No.2 (Course STA301) Fall 2012 

Question 1: 

A)The fourth mean moment of a symmetric distribution is 243. What would be the value of the standard deviation in order that the distribution may be meso-kurtic?

SOLUTION:-
Standard is equal to 2nd moment
We are that m4 = 243 . Therefore
m4 = 243
m4/m2 = b3 = 3  i.e   = 243/m2^2 = 3
or 243/3 = 81 or m2 = 9
Standard deviation is equal to m  2nd moment


B)Two candidates X and Y at the B.A (Hons.) Examination obtained the following data.

Candidate X Candidate Y   
 = 43.2 =        20.5   
S.D = 24.25   S.D = 15.6  
Which of the candidate showed a more consistent performance?
SOLUTION:-
By calculating the co-efficient of variation in each case.
Candidate A
C V = s/x * 100
C V = 24.25/43.2 * 100
C V = 56.13%
Candidate B
C V = s/y * 100
C V = 15.6/20.5*100
C V = 76.097%

We see that co­efficient of variation for the candidate A smaller than that for the
candidate B.Hence candidate A is more consistent than candidate B


Question 2:

A)If coefficient of skewness = 0, then what would you say about the shape of the distribution?
SOLUTION:-
For symmetric distributions or curves, the coefficient is zero. The shape is symmetric
B)The following data were computed from personnel records of a manufacturing firm:
             X = Number of years of service
            Y = weekly wage rate
          n = 23; ∑X = 2433; ∑Y = 4254, ∑   = 281019;   = 841786 and  = 482788
 If the correlation coefficient indicates that there does exist a relationship between X and Y,                                    compute the least squares line of regression Y = a + b X. 
SOLUTION:-
Where bxy = n (XY)-(X)(Y) / n (X^2)-(X)^2

bxy = 23(482788) (2433)(4254) / 23(281019) (2433)^2
bxy = 11104124-10349982 / 6463437-5919489
bxy = 754142/543948
b     = 1.3864
a     = y-bx

y   = ¥y/n = 
4254/23 = 
184.96


x  = 
¥x/n = 
2433/23 = 105.78

a = 184.96-1.39(105.78)
a = 184.96-147.0342
a = 37.92
Hence
y  = 37.92+1.39X
Is estimated regression equation appropriate for predicting the no
of years (x) given weekly wage rate