129/138
20/80 = 1/4
1184/1399
They are (A) Dependent because P(Losing weight) is likely different than P(Losing weight | Going to the gym)
choose(8,3)*choose(7,3)*3
## [1] 5880
They are (B) Independent
14!/(14-8)! = 121,080,960
round( (4/22 * 9/23 * 8/22 * 7/21 *6/20) * 4, 4)
## [1] 0.0103
factorial(11)/factorial(7)
## [1] 7920
33 percent of subscribers to a fitness magazine are not over the age of 34.
p_W <- 0.5^4 * choose(4, 3)
#Step 1.
EV <- p_W * 97 - (1-p_W) * 30
EV
## [1] 1.75
#Step 2.
EV * 559
## [1] 978.25
p_W <- sum(dbinom(4:0, 9, 0.5))
#Step 1.
EV <- p_W * 23 - (1-p_W) * 26
EV
## [1] -1.5
#Step 2.
EV * 994
## [1] -1491
p_liar = 0.2
p_truther = 1-p_liar
p_liar_and_detect = p_liar * 0.59
p_truther_and_detect = p_truther * 0.90
cont_tbl <- data.frame(Detect_Lie = c(p_liar_and_detect, p_truther-p_truther_and_detect),
Detect_Truth = c(p_liar-p_liar_and_detect, p_truther_and_detect),
row.names = c("Liar", "Truth_Teller"))
cont_tbl
## Detect_Lie Detect_Truth
## Liar 0.118 0.082
## Truth_Teller 0.080 0.720
###(a)
cont_tbl["Liar", "Detect_Lie"] / (cont_tbl["Liar", "Detect_Lie"] + cont_tbl["Truth_Teller", "Detect_Lie"])
## [1] 0.5959596
###(b)
cont_tbl["Truth_Teller", "Detect_Truth"] / (cont_tbl["Truth_Teller", "Detect_Truth"] + cont_tbl["Liar", "Detect_Truth"])
## [1] 0.8977556
###(c)
# This is just P(Liar&Detect_Lie) or P(Liar&Detect_Truth) or P(Truth_Teller&Detect_Lie)
cont_tbl["Liar", "Detect_Lie"] + cont_tbl["Liar", "Detect_Truth"] + cont_tbl["Truth_Teller", "Detect_Lie"]
## [1] 0.28