getwd()## [1] "C:/Quiz"
library(ggplot2)
library(dplyr)load("brfss2013.RData")1.1 number of observations that are “NA” in the variable “sleptim1”
total_obs <- nrow(brfss2013)
brfss2013 %>%
group_by(sleptim1) %>%
filter(is.na(sleptim1) )%>%
summarise(count=n())## # A tibble: 1 × 2
## sleptim1 count
## <int> <int>
## 1 NA 7387
1.2 number of observations having at most 5 hours of sleep;
brfss2013 %>%
group_by(sleptim1) %>%
filter(sleptim1 <= 5)%>%
summarise(frequency=n())## # A tibble: 6 × 2
## sleptim1 frequency
## <int> <int>
## 1 0 1
## 2 1 228
## 3 2 1076
## 4 3 3496
## 5 4 14261
## 6 5 33436
x <- brfss2013 %>%
group_by(sleptim1) %>%
filter(sleptim1 <= 5)%>%
summarise(frequency=n())sum(x$frequency)## [1] 52498
1.3 number of observations having more than 5 hours of sleep but less than 11 hours of sleep;
xx <- brfss2013 %>%
group_by(sleptim1) %>%
filter(sleptim1 > 5)%>%
filter(sleptim1 < 11)%>%
summarise(frequency=n())xx## # A tibble: 5 × 2
## sleptim1 frequency
## <int> <int>
## 1 6 106197
## 2 7 142469
## 3 8 141102
## 4 9 23800
## 5 10 12102
sum(xx$frequency)## [1] 425670
1.4 number of observations having at least 11 hours of sleep;
xxx <- brfss2013 %>%
group_by(sleptim1) %>%
filter(sleptim1 >= 11)%>%
filter(sleptim1 <= 24)%>%
summarise(frequency=n())xxx## # A tibble: 14 × 2
## sleptim1 frequency
## <int> <int>
## 1 11 833
## 2 12 3675
## 3 13 199
## 4 14 447
## 5 15 367
## 6 16 369
## 7 17 35
## 8 18 164
## 9 19 13
## 10 20 64
## 11 21 3
## 12 22 10
## 13 23 4
## 14 24 35
sum(xxx$frequency)## [1] 6218
1.5 numbers of observation having at most 5 hours of sleep that are married;
xxxx <- brfss2013 %>%
group_by(sleptim1) %>%
filter(sleptim1 <= 5, marital == "Married")%>%
summarise(frequency=n())xxxx## # A tibble: 5 × 2
## sleptim1 frequency
## <int> <int>
## 1 1 61
## 2 2 302
## 3 3 1120
## 4 4 5452
## 5 5 14482
sum(xxxx$frequency)## [1] 21417