LECTURE 3 - 22nd Jan 2013

ASSIGNMENT 1a) - GROOVE MILAGE DATA

Fit 'lm' and comment on the applicability of lm.
Plot : Residual vs Independent curve
Plot: Standard residual vs Independent curve

As the plot is random, Linearity is applicability.

ASSIGNMENT 2) : Using the given data of alpha - pluto, Fit 'lm' and comment on its applicability

Plot is Random. 

Hence Linearity is applicable.

ASSIGNMENT 3 : Justify NUll Hypothesis using ANOVA

Analysis of the result : 
P value is 0.687%
High P value. Thus there is not sufficient information to reject the null hypothesis.

LECTURE 2 - 16TH JAN 2013

QUESTION 1 : 

CREATE 2 MATRICES OF DIMENSION [3X3]. SELECT THE SECOND COLUMN IN THE FIRST MATRIX & THE THIRD COLUMN IN THE SECOND MATRIX. USE CBIND TO COMBINE THE SELECTED COLUMNS

QUESTION 2 :

MULTIPLY 2 MATRICES

QUESTION 3 : 

DOWNLOAD NSE DATA FOR A PERIOD OF 31 DAYS, SAY FROM 1ST DECEMBER 2012 TO 31ST DECEMBER 2012. FIND REGRESSION.

 

QUESTION 4 : 

GENERATE & PLOT NORMAL DISTRIBUTION GRAPH

> x<-seq(0,300)
> y<-dnorm(x,mean=100,sd=20)
> plot(x,y,type=”l”)

INTRODUCTION TO R - Lecture 1

Plot line of 1-D Array

x<-c(1,2,3)

plot(x, type="l")

Plot Histogram of 1-D Array

x<-c(1,2,3)

plot(x, type="h")

Question 1 : Plot Histogram of 1 column of NSE Data 

zcol1<-z[,3]

plot(zcol1,type="h")

Question 2 : Plot the above in Line & Point form with X axis & Y- axis and Label

plot(zcol1,type="b", main = "NSE GRAPH", xlab="Time", ylab="Value")

Question 3 : ScatterPlot of Low & High Values of NSE data

zcol1<-z[,3]

zcol2<-z[,4]

plot(zcol1,zcol2)

Question 4 : Volatility in the data