#################################################

# 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