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ppois(10,4.5)
## [1] 0.9933313
plot(0:10, dpois(0:10, 4.5), main = "Binomial PMF", xlab = "n", ylab = "")

1b. We can find the probabilty of 3 or fewer breakdowns by looking at the first part of the graph up until x=3

  1. Re-analyze question 11
curve(dnorm(x, 200, 30), 120, 280, main = "Normal PDF ", 
      xlab = "Weight", 
      ylab = "Package Storage")

In the above graph we can see that the package weights are normally distributed with most of the packages being at or around the target 200g.

pnorm
## function (q, mean = 0, sd = 1, lower.tail = TRUE, log.p = FALSE) 
## .Call(C_pnorm, q, mean, sd, lower.tail, log.p)
## <bytecode: 0x0000018492069b30>
## <environment: namespace:stats>

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