survey results - Chad Randall

This survey was placed to graph the military versus non-military alcohol use. I surmised that military members would be more apt to drink more than their civilian counterparts. I utilized google forms and facebook to distribute this survey.

library(tidyverse)

library(readxl)
alcohol <- read_excel("alcohols.xlsx")
glimpse(alcohol)

Observations: 57
Variables: 10
$ Timestamp                                                                                    <dttm> …
$ military                                                                                     <chr> …
$ `What is your gender?`                                                                       <chr> …
$ `What is your age range?`                                                                    <chr> …
$ `How often do you drink a week?`                                                             <chr> …
$ `When you drink, how many drinks do you USUALLY consume`                                     <dbl> …
$ `How many times a month do you binge drink (5 drinks in one sitting)`                        <chr> …
$ `If you drink, how long ago has it been since you blacked out (drinking until unconscious)?` <chr> …
$ `Do you feel like you have a drinking problem?`                                              <chr> …
$ `Is alcohol a factor in having fun in social settings?`                                      <chr> …

alcohol <-alcohol %>% 
  rename (age = "What is your age range?") %>% 
  rename (gender = "What is your gender?") %>% 
  rename (party = "Is alcohol a factor in having fun in social settings?") %>% 
  rename (frequency = "How often do you drink a week?")

alcohol <- alcohol %>% 
  mutate(military = fct_recode(military, "Military" = "1", "No military" = "2"))

Unknown levels in `f`: 1, 2

alcohol %>% 
  count(military)

alcohol <- alcohol %>% 
  mutate(frequency = fct_recode(frequency, "never" = "0", " to 2 times a week" = "1", "3 to 5 times a week" = "2", "6 to 7 times a week" = "3"))

Unknown levels in `f`: 0, 1, 2, 3

alcohol %>% 
  count(frequency)

This chart shows the frequency of Military and no military members

alcohol %>% 
  drop_na(frequency) %>% 
  ggplot(aes(x = military, fill = frequency)) +
  geom_bar(position = "dodge")+
  scale_fill_viridis_d()+
  coord_flip()+
  theme_minimal()

This graph represents the frequency use of alcohol based on the ages of participants.

alcohol %>% 
  drop_na(frequency) %>% 
  ggplot(aes(x = age, fill = frequency)) +
  geom_bar(position = "dodge")+
  scale_fill_viridis_d()+
  coord_flip()+
  theme_minimal()+
  labs(y = "Age", 
       x = "Number of participants", 
       title = "Age vs. Alcohol use")

This graph shows the thoughts on alcohol during social settings.

alcohol %>% 
  drop_na(party) %>% 
  ggplot(aes(x = military, fill = party)) +
  geom_bar(position = "dodge")+
  scale_fill_viridis_d()+
  coord_flip()+
  theme_minimal()+
  labs(y = "military", 
       x = "alcohol at social events", 
       title = "military vs. non-military alcohol in social settings")

This graph shows the gender differences in uses

alcohol %>% 
  drop_na(gender) %>% 
  ggplot(aes(x = frequency, fill = gender)) +
  geom_bar(position = "dodge")+
  scale_fill_viridis_d()+
  coord_flip()+
  theme_minimal()+
  labs(y = "gender", 
       x = "frequency", 
       title = "gender frequency uses")