15th Jan,2013
Assignment 1 -:
To bind columns/rows from 2 different matrices into a new matrix
Sol -:
Matrix 1 assignment and generation
> mat1<-c(1:10)
> dim(mat1)<-c(2,5)
Matrix 2 assignment and generation
> mat2<-c(11:16)
> dim(mat2)<-c(2,3)
Taking 3 column from matrix1 and 2nd column from matrix 2
Binding using the cbind and rbind functions as shown -:
Assignment 2
Multiply 2 matrices
Sol -:
Command to multiply 2 matrices
> multip <- z1 %*% z2
Assignment 3-:
To read NSE historical data dated from 1st Dec, 2012 to 31st Dec, 2012 from a .csv file.
To find regression between the High Price and the opening share price and also calculating the residuals.
Soln- :
Command For Regression :
> reg1<-lm(HighPrice ~ OpenPrice , data = NSEData)
NSEData - Object with file historical data
High Price - Dependent variable
Open Price - Independent variable
Residuals
Assignment 4
To generate data for a normal distribution and plot the distribution curve
Soln -:
To generate normally distributed random numbers function used is -:
rnorm(N, mean,sd)
where N is the no of observations
mean is the mean vector
sd - standard deviation
As shown below -:
The plot is as shown -:
Assignment 1 -:
To bind columns/rows from 2 different matrices into a new matrix
Sol -:
Matrix 1 assignment and generation
> mat1<-c(1:10)
> dim(mat1)<-c(2,5)
Matrix 2 assignment and generation
> mat2<-c(11:16)
> dim(mat2)<-c(2,3)
Taking 3 column from matrix1 and 2nd column from matrix 2
Binding using the cbind and rbind functions as shown -:
Assignment 2
Multiply 2 matrices
Sol -:
Command to multiply 2 matrices
> multip <- z1 %*% z2
Assignment 3-:
To read NSE historical data dated from 1st Dec, 2012 to 31st Dec, 2012 from a .csv file.
To find regression between the High Price and the opening share price and also calculating the residuals.
Soln- :
Command For Regression :
> reg1<-lm(HighPrice ~ OpenPrice , data = NSEData)
NSEData - Object with file historical data
High Price - Dependent variable
Open Price - Independent variable
Residuals
Assignment 4
To generate data for a normal distribution and plot the distribution curve
Soln -:
To generate normally distributed random numbers function used is -:
rnorm(N, mean,sd)
where N is the no of observations
mean is the mean vector
sd - standard deviation
As shown below -:
The plot is as shown -:






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