11.2: Conditional Probability (Section 10.4)
- Page ID
- 8782
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\(\newcommand{\avec}{\mathbf a}\) \(\newcommand{\bvec}{\mathbf b}\) \(\newcommand{\cvec}{\mathbf c}\) \(\newcommand{\dvec}{\mathbf d}\) \(\newcommand{\dtil}{\widetilde{\mathbf d}}\) \(\newcommand{\evec}{\mathbf e}\) \(\newcommand{\fvec}{\mathbf f}\) \(\newcommand{\nvec}{\mathbf n}\) \(\newcommand{\pvec}{\mathbf p}\) \(\newcommand{\qvec}{\mathbf q}\) \(\newcommand{\svec}{\mathbf s}\) \(\newcommand{\tvec}{\mathbf t}\) \(\newcommand{\uvec}{\mathbf u}\) \(\newcommand{\vvec}{\mathbf v}\) \(\newcommand{\wvec}{\mathbf w}\) \(\newcommand{\xvec}{\mathbf x}\) \(\newcommand{\yvec}{\mathbf y}\) \(\newcommand{\zvec}{\mathbf z}\) \(\newcommand{\rvec}{\mathbf r}\) \(\newcommand{\mvec}{\mathbf m}\) \(\newcommand{\zerovec}{\mathbf 0}\) \(\newcommand{\onevec}{\mathbf 1}\) \(\newcommand{\real}{\mathbb R}\) \(\newcommand{\twovec}[2]{\left[\begin{array}{r}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\ctwovec}[2]{\left[\begin{array}{c}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\threevec}[3]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\cthreevec}[3]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\fourvec}[4]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\cfourvec}[4]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\fivevec}[5]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\cfivevec}[5]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\mattwo}[4]{\left[\begin{array}{rr}#1 \amp #2 \\ #3 \amp #4 \\ \end{array}\right]}\) \(\newcommand{\laspan}[1]{\text{Span}\{#1\}}\) \(\newcommand{\bcal}{\cal B}\) \(\newcommand{\ccal}{\cal C}\) \(\newcommand{\scal}{\cal S}\) \(\newcommand{\wcal}{\cal W}\) \(\newcommand{\ecal}{\cal E}\) \(\newcommand{\coords}[2]{\left\{#1\right\}_{#2}}\) \(\newcommand{\gray}[1]{\color{gray}{#1}}\) \(\newcommand{\lgray}[1]{\color{lightgray}{#1}}\) \(\newcommand{\rank}{\operatorname{rank}}\) \(\newcommand{\row}{\text{Row}}\) \(\newcommand{\col}{\text{Col}}\) \(\renewcommand{\row}{\text{Row}}\) \(\newcommand{\nul}{\text{Nul}}\) \(\newcommand{\var}{\text{Var}}\) \(\newcommand{\corr}{\text{corr}}\) \(\newcommand{\len}[1]{\left|#1\right|}\) \(\newcommand{\bbar}{\overline{\bvec}}\) \(\newcommand{\bhat}{\widehat{\bvec}}\) \(\newcommand{\bperp}{\bvec^\perp}\) \(\newcommand{\xhat}{\widehat{\xvec}}\) \(\newcommand{\vhat}{\widehat{\vvec}}\) \(\newcommand{\uhat}{\widehat{\uvec}}\) \(\newcommand{\what}{\widehat{\wvec}}\) \(\newcommand{\Sighat}{\widehat{\Sigma}}\) \(\newcommand{\lt}{<}\) \(\newcommand{\gt}{>}\) \(\newcommand{\amp}{&}\) \(\definecolor{fillinmathshade}{gray}{0.9}\)Let’s determine the conditional probability of someone being unhealthy, given that they are over 70 years of age, using the NHANES dataset. Let’s create a new data frame that
healthDataFrame <-
NHANES %>%
mutate(
Over70 = Age > 70,
Unhealthy = DaysPhysHlthBad > 0
) %>%
dplyr::select(Unhealthy, Over70) %>%
drop_na()
glimpse(healthDataFrame)## Observations: 4,891
## Variables: 2
## $ Unhealthy <lgl> FALSE, FALSE, FALSE, TRUE, FALSE, TRUE,…
## $ Over70 <lgl> FALSE, FALSE, FALSE, FALSE, FALSE, FALS…First, what’s the probability of being over 70?
pOver70 <-
healthDataFrame %>%
summarise(pOver70 = mean(Over70)) %>%
pull()
# to obtain the specific value, we need to extract it from the data frame
pOver70## [1] 0.11Second, what’s the probability of being unhealthy?
pUnhealthy <-
healthDataFrame %>%
summarise(pUnhealthy = mean(Unhealthy)) %>%
pull()
pUnhealthy## [1] 0.36What’s the probability for each combination of unhealthy/healthly and over 70/ not? We can create a new variable that finds the joint probability by multiplying the two individual binary variables together; since anything times zero is zero, this will only have the value 1 for any case where both are true.
pBoth <- healthDataFrame %>%
mutate(
both = Unhealthy*Over70
) %>%
summarise(
pBoth = mean(both)) %>%
pull()
pBoth## [1] 0.043Finally, what’s the probability of someone being unhealthy, given that they are over 70 years of age?
pUnhealthyGivenOver70 <-
healthDataFrame %>%
filter(Over70 == TRUE) %>% # limit to Over70
summarise(pUnhealthy = mean(Unhealthy)) %>%
pull()
pUnhealthyGivenOver70## [1] 0.38# compute the opposite:
# what the probability of being over 70 given that
# one is unhealthy?
pOver70givenUnhealthy <-
healthDataFrame %>%
filter(Unhealthy == TRUE) %>% # limit to Unhealthy
summarise(pOver70 = mean(Over70)) %>%
pull()
pOver70givenUnhealthy## [1] 0.12