tbl = table(exdata$MedHxMarijStatusCurrent, exdata$Race, exdata$Sex)
tbl

## , ,  = Women
## 
##    
##     White AfrAm
##   0   622   810
##   1    47   101
## 
## , ,  = Men
## 
##    
##     White AfrAm
##   0   455   563
##   1    61   142

t-test for marijuana use and age

x = exdata$MedHxMarijStatusCurrent
y = exdata$Age0
t.test(y~x)

## 
##  Welch Two Sample t-test
## 
## data:  y by x
## t = 7.627, df = 475, p-value = 1.324e-13
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  2.794 4.734
## sample estimates:
## mean in group 0 mean in group 1 
##           48.53           44.76

chi-square for marijuana use and sex

tbl = table(exdata$MedHxMarijStatusCurrent,exdata$Sex)
tbl

##    
##     Women  Men
##   0  1432 1018
##   1   148  203

chisq.test(tbl)

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  tbl
## X-squared = 32.45, df = 1, p-value = 1.224e-08

chi-square for marijuana use and race

tbl = table(exdata$MedHxMarijStatusCurrent,exdata$Race)
tbl

##    
##     White AfrAm
##   0  1077  1373
##   1   108   243

chisq.test(tbl)

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  tbl
## X-squared = 21.35, df = 1, p-value = 3.834e-06

chi-square for marijuana use and poverty status

tbl = table(exdata$MedHxMarijStatusCurrent,exdata$PovStat)
tbl

##    
##     Above Below
##   0  1465   985
##   1   194   157

chisq.test(tbl)

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  tbl
## X-squared = 2.42, df = 1, p-value = 0.1198