1) Wrangle the data frame to obtain all rows where pH > 6.930 and select the variables WellClass and Aquifier to use in a table.
stats_quiz tables wrangle and dpqr
Estimate P(Bedrock | Public) for wells that have a pH > 6.930
library(dplyr)
df1 = mtbe %>% filter(pH > 6.930) %>% select(WellClass, Aquifier)
tab1 = with(df1, table(WellClass, Aquifier))
addmargins(tab1)
Aquifier
WellClass Bedrock Unconsoli Sum
Private 78 0 78
Public 80 9 89
Sum 158 9 167
round(80/89,4)2) Filter the original mtbe data frame to obtain all rows where 47.244 < Depth < 121.920 and and select variables WellClass and MTBE-Detect.
stats_quiz tables wrangle and dpqr
Estimate P(Public AND Below Limit) for wells that have a depth between 47.244 and 121.920
> df2 <- mtbe %>% filter(Depth > 47.244 & Depth < 121.920) %>% select(WellClass, `MTBE-Detect`)
> tab2 <- with(df2, table(WellClass, `MTBE-Detect`))
> addmargins(tab2)
MTBE-Detect
WellClass Below Limit Detect Sum
Private 31 10 41
Public 29 19 48
Sum 60 29 89
round(29/89,4)
[1] 0.32583) If X ~ Bin(n = 10, p = 0.6) find P(X = 7)
> dbinom(7,10,0.6)
[1] 0.21499084) If Y ~ Bin(n = 20, p=0.5) find P(Y < 9
> pbinom(8,20,0.5)
[1] 0.2517223