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August 30, 2017 16:44
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R Tutorial For Beginners
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# Here we view that many random trials result in a Gaussian Distribution. | |
# first we create random vector and resize it be a matrix | |
d2 <- runif(4000,-1,2) | |
dim(d2) <- c(100,40) | |
#wanna see my d2? | |
head(d2) | |
#now we bind the a new column rowsum to the original matrix (Column 41!) | |
sumz <- rowSums(d2) | |
d2 <- cbind(d2, sumz) | |
#take a peek! | |
head(d2) | |
x <- sumz | |
#we be histogrammin' | |
h<-hist(x, breaks=10, col="green", xlab="Sum of 40 trials", | |
main="Histogram with Normal Curve") | |
#we fit a calculated normal distribution to this data | |
xfit<-seq(min(x),max(x),length=40) #must fit the dimensions | |
yfit<-dnorm(xfit,mean=mean(x),sd=sd(x)) #here the calculations happen (mean, sd) | |
yfit <- yfit*diff(h$mids[1:2])*length(x) #the points are added at the mid-point of the histogram bars | |
#and finally the lines are overlaid over the histogram. HUZZAH | |
lines(xfit, yfit, col="blue", lwd=3) # | |
#code adapted from http://www.statmethods.net/graphs/density.html |
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