library(tidyverse)
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr 1.2.1 ✔ readr 2.2.0
## ✔ forcats 1.0.1 ✔ stringr 1.6.0
## ✔ ggplot2 4.0.3 ✔ tibble 3.3.1
## ✔ lubridate 1.9.5 ✔ tidyr 1.3.2
## ✔ purrr 1.2.2
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
library(readxl)
library(pastecs)
##
## Attaching package: 'pastecs'
##
## The following objects are masked from 'package:dplyr':
##
## first, last
##
## The following object is masked from 'package:tidyr':
##
## extract
load("NSDUH_2023.Rdata")
pastecs::stat.desc(data$`BNGDRMDAYS`)
## x
## nbr.val 5.670500e+04
## nbr.null 0.000000e+00
## nbr.na 0.000000e+00
## min 1.000000e+00
## max 5.000000e+00
## range 4.000000e+00
## sum 2.428770e+05
## median 5.000000e+00
## mean 4.283167e+00
## SE.mean 5.994653e-03
## CI.mean.0.95 1.174955e-02
## var 2.037743e+00
## std.dev 1.427495e+00
## coef.var 3.332803e-01
BNGDRMDAYS measures the frequency of binge alcohol use during the past 30 days.
data<- data %>% drop_na(`BNGDRMDAYS`)
data<- data %>% filter(BNGDRMDAYS>0)
head(data$BNGDRMDAYS)
## [1] 3 2 5 5 5 5
hist(data$BNGDRMDAYS)
data<-data%>%mutate(LOG_CFS=log(BNGDRMDAYS))%>%
select(BNGDRMDAYS,LOG_CFS)
head(data)
## # A tibble: 6 × 2
## BNGDRMDAYS LOG_CFS
## <dbl> <dbl>
## 1 3 1.10
## 2 2 0.693
## 3 5 1.61
## 4 5 1.61
## 5 5 1.61
## 6 5 1.61
hist(data$LOG_CFS)