Assignment -session 2 15/01/13

   Assignment-2

Assignment1:

a. Create two matrices
b. Select two columns
c. Use cbind to create a new matrix

solution:
a)  z<-c(19,10,15,100,32,56,28,29,91)
> dim(z)<-c(3,3)
> z
     [,1] [,2] [,3]
[1,]   19  100   28
[2,]   10   32   29
[3,]   15   56   91
> m<-c(1,2,3,4,4,5,5,6,6)
> dim(m)<-c(3,3)
> m
     [,1] [,2] [,3]
[1,]    1    4    5
[2,]    2    4    6
[3,]    3    5    6

b)

 x<- z[,3]

 y<-m[,3]

c) cbind(x,y)

      x y

[1,] 28 5

[2,] 29 6

[3,] 91 6

Assignment2

a. Multiply matrix1 and matrix2

solution:-

 mul<-z%*%m

> mul

     [,1] [,2] [,3]

[1,]  303  616  863

[2,]  161  313  416

[3,]  400  739  957

Assignment3

a.)Regression of NSE downloaded data 01/12/12-31/21/12

> data<- read.csv(file.choose(),header=T)

> data

 high<- data[,3]

> high

 [1] 5899.15 5894.95 5917.80 5942.55 5949.85 5919.95 5965.15 5924.60 5907.45

[10] 5886.10 5886.05 5905.80 5939.40 5937.60 5888.00 5871.90 5917.30 5930.80

[19] 5915.75 5919.00

open<- data[,2]

open

 [1] 5878.25 5866.80 5906.60 5926.30 5934.00 5916.05 5923.80 5917.80 5900.35

[10] 5846.90 5860.50 5873.60 5917.30 5934.45 5888.00 5869.00 5864.95 5930.20

[19] 5887.15 5901.20

 ans<-cbind(open,high)

> ans

         open    high

 [1,] 5878.25 5899.15

 [2,] 5866.80 5894.95

 [3,] 5906.60 5917.80

 [4,] 5926.30 5942.55

 [5,] 5934.00 5949.85

 [6,] 5916.05 5919.95

 [7,] 5923.80 5965.15

 [8,] 5917.80 5924.60

 [9,] 5900.35 5907.45

[10,] 5846.90 5886.10

[11,] 5860.50 5886.05

[12,] 5873.60 5905.80

[13,] 5917.30 5939.40

[14,] 5934.45 5937.60

[15,] 5888.00 5888.00

[16,] 5869.00 5871.90

[17,] 5864.95 5917.30

[18,] 5930.20 5930.80

[19,] 5887.15 5915.75

[20,] 5901.20 5919.00

>  

 reg1<-lm(high~open,data=data)

 reg1

Call:

lm(formula = high ~ open, data = data)

Coefficients:

(Intercept)         open  

  1578.3358       0.7355  

The regression Image is as follows

Assignment 4: Plotting a normal distribution for the data.

solution :-