Functions from stat package (which is loaded by
default).
The probability mass at a point \(x\) can be evaluated using the syntax:
dnorm(x=x,mean=m,sd=s).
The probability distribution \(P(X\leq
x)\) is calculated using the pnorm() function.
Syntax is:
pnorm(x,mean=m,sd=s)
The quantile for probability \(p\)
can be evaluated using the qnorm() function. Syntax is:
qnorm(prob,mean=m,sd=s)
Step 1: Assign the inputs for required distribution
Step 2: Calculate the required probabilities
Step 3: Report the results
Case: Generate and draw the cdf and pdf of a normal distribution with mean=10 and standard deviation=3. Use values of \(x\) from 0 to 20 in intervals of 1.
# create input parameters
t=seq(0,20,1); mu=10;sd=3
#calculating probability mass distribution and cumulative distribution
pmval=dnorm(t,mean = mu,sd=sd)
pmval
## [1] 0.000514093 0.001477283 0.003798662 0.008740630 0.017996989 0.033159046
## [7] 0.054670025 0.080656908 0.106482669 0.125794409 0.132980760 0.125794409
## [13] 0.106482669 0.080656908 0.054670025 0.033159046 0.017996989 0.008740630
## [19] 0.003798662 0.001477283 0.000514093
#calculating cumulative density
cdval=pnorm(t,mean = mu,sd=sd)
cdval
## [1] 0.0004290603 0.0013498980 0.0038303806 0.0098153286 0.0227501319
## [6] 0.0477903523 0.0912112197 0.1586552539 0.2524925375 0.3694413402
## [11] 0.5000000000 0.6305586598 0.7475074625 0.8413447461 0.9087887803
## [16] 0.9522096477 0.9772498681 0.9901846714 0.9961696194 0.9986501020
## [21] 0.9995709397
pmf and cdfpar(mfrow=c(1,2))
plot(t,pmval,xlab="t",ylab="P(X=t)", main="The Normal Distribution")
plot(t,cdval,xlab="t",ylab=expression(P(X<=t)),main="Cumulative Distribution Function")
The pmf and cf of the Normal distribution
for given input parameters are evaluated and create respective
plots.