#################################################
# SELECTED PRACTICE PROBLEMS USING R -SCHAUMS
#################################################
# P.49-50
# 3.1
sales<-c(.10,.10,.25,.25,.25,.35,.40,.53,.90,1.25,1.35,2.45,2.71,3.09,4.10)
summary(sales)
sum(sales)
#3.5
salary<-c(240,240,240,240,240,240,240,240,255,255,265,265,280,280,290,300,305,325,330,340)
sum(salary)# just to check your work done by hand
summary(salary)
#---------------------------------
# EXAMPLE OF HISTOGRAM
#---------------------------------
library(lattice)# graphing package
hist(salary) # graph histogram
d <- density(salary) # fit curve to data
plot(d) # plot curve
# 4.9
minutes<-c(5,5,5,7,9,14,15,15,16,18)
print(minutes)
summary(minutes)
var(minutes)
sd(minutes)
library(lattice) # for graphics,but not necessary if previously loaded
hist(minutes)
d<-density(minutes)
plot(d)
#4.24
weights<-c(21,18,30,12,14,17,28,10,16,25)
sum(weights)
summary(weights)
sum(weights*weights) gives sum of X squared
var(weights)
sd(weights)
#4.33
cars<-c(2,4,7,10,10,10,12,12,14,15)
print(cars)
sum(cars)
summary(cars)
sum(cars*cars)
var(cars)
sd(cars)
(4.16866/9.6)*100 #co-efficient of variation
#################################################
# SELECTED PRACTICE PROBLEMS USING R -WILLIAMS
#################################################
#P.107
#1a
sample<-c(10,20,12,17,16)
print(sample)
summary(sample)
#2a
sample<-c(10,20,21,17,16,12)
print(sample)
summary(sample)
#p.151
#61
loans<-c(10.1,14.8,5,10.2,12.4,12.2,2,11.5,17.8,4)
print(loans)
sum(loans)
summary(loans)
sum(loans^2)
var(loans)
sd(loans)
#63
public<-c(28,29,32,37,33,25,29,32,41,34)
print(public)
sum(public)
summary(public)
sum(public^2)
var(public)
sd(public)
(4.64/32)*100 #CV
auto<-c(29,31,33,32,34,30,31,32,35,33)
print(auto)
sum(auto)
summary(auto)
sum(auto^2)
var(auto)
sd(auto)
(1.83/3.33)*100 #CV