Speciality Toys Managerial Report

This report helps the higher management to forecast the inventory for the Teddy Toy

The management team members have suggested order quantities 15k,18k,24k,28k

Senior forecaster has predicted an expected demand of 20k

Demand would be between 10 and 30k .95 probability

.95 probability in normal distribution has a Z score of 1.96

Calculating Std Deviation using the formula = (x-mean)sd

z=1.96

x=30000

mean= 20000

sd= (x-mean)/z

Generating a normal distribution using mean = 20000 and SD =5102

vec=rnorm(1000,20000,sd)

density=dnorm(vec,mean,sd)

df=data.frame(vec)

Plotting Distribution

hist(vec)

library(ggplot2)

ggplot(df,aes(df$vec))+geom_histogram( aes(y =..density..),

                                      col="red", 
                                      fill="green", 
                                      alpha = .2,binwidth = 500)+ geom_density(col=2) 

myplot = ggplot(df,aes(df$vec)) 
myplot = myplot + geom_density(fill="yellow",inherit.aes = TRUE,adjust=3,show.legend = TRUE)
 myplot = myplot+ geom_vline(aes(xintercept = mean,colour="mean"))
myplot = myplot +geom_vline(aes(xintercept = mean-sd,colour="stand"))
myplot = myplot +geom_vline(aes(xintercept = mean+sd,colour="stand"))
myplot=myplot+  geom_text(aes(x=mean-200, label="Mean",y= mean(density)),angle=90)

myplot=myplot+  geom_text(aes(x=(mean-sd)-200, label="Mean - Sigma",y= mean(density)),angle=90)
myplot=myplot+  geom_text(aes(x=(mean+sd)-200, label="Mean + Sigma",y= mean(density)),angle=90)



myplot

#, colour="blue", angle=90, vjust = 1.2)

#ggplot(df,aes(df$vec)) +stat_density()

Probailitiy for Stock Out order quantities

orderQty=c(15000,18000,24000,28000)
probs=1-pnorm(orderQty,mean,sd)

probqty=cbind(orderQty,probs)

probqty

##      orderQty      probs
## [1,]    15000 0.83645694
## [2,]    18000 0.65247089
## [3,]    24000 0.21652006
## [4,]    28000 0.05844057