Case-II: Lifestyle and Sleeping Quality

Part A General Summary

Hi Jacskon

#Reading the file 
sleep<-read.csv("sleep.csv")
coljack<-c(
  
"#33ccff",
"#33ffbb",
"#33ff33",
"#99ff33",
"#ff9933",
"#ff3333",
"#ff3399",
"#ff33ff",
"#7733ff",
"#3333ff",
"#ffff1a"
  
  )
#Types of Jobs at a study 
unique(sleep$occupation)
 [1] "Software Engineer"    "Doctor"               "Sales Representative"
 [4] "Teacher"              "Nurse"                "Engineer"            
 [7] "Accountant"           "Scientist"            "Lawyer"              
[10] "Salesperson"          "Manager"             
#Types of Sleep disorders in the study 
unique(sleep$sleep_disorder)
[1] "None"        "Sleep Apnea" "Insomnia"   
#Range of sleep quality 
sort(unique(sleep$sleep_quality))
[1] 4 5 6 7 8 9
#Sample size 
print(sample_size<-length(sleep$gender))
[1] 374
#Mean of sleep time
print(mean_sleepdur<-mean(sleep$sleep_duration))
[1] 7.132086
boxplot(sleep$age,horizontal =TRUE,col="lightblue",main="Age of sample")

sleepocdu<-aggregate( sleep_duration ~ occupation, data = sleep, FUN = mean)
sleepocdu <- sleepocdu[order(-sleepocdu$sleep_duration),]
print(sleepocdu)
             occupation sleep_duration
3              Engineer       7.987302
4                Lawyer       7.410638
1            Accountant       7.113514
6                 Nurse       7.063014
2                Doctor       6.970423
5               Manager       6.900000
10    Software Engineer       6.750000
11              Teacher       6.690000
8           Salesperson       6.403125
9             Scientist       6.000000
7  Sales Representative       5.900000
par(mar = c(5, 4, 4, 2))  # smaller bottom margin now


bpsd <- barplot(
  sleepocdu$sleep_duration,
  col = coljack
,
  main = "Sleep duration based on Profession",
  axis.lty = 0,
  ylim = c(0, 10),
  ylab = "Sleep (Hours)",
  xlab= "Occupation"
)


text(
  x = bpsd,
  y = sleepocdu$sleep_duration + 0.3,
  labels = sleepocdu$occupation,
  srt = 90,      
  adj = 0,
  cex = 1
)

Engineer is with the highest duration of sleep on average








sleepocqw<-aggregate( sleep_quality ~ occupation, data = sleep, FUN = mean)
sleepocqw <- sleepocqw[order(-sleepocqw$sleep_quality),]
print(sleepocqw)
             occupation sleep_quality
3              Engineer      8.412698
4                Lawyer      7.893617
1            Accountant      7.891892
6                 Nurse      7.369863
5               Manager      7.000000
11              Teacher      6.975000
2                Doctor      6.647887
10    Software Engineer      6.500000
8           Salesperson      6.000000
9             Scientist      5.000000
7  Sales Representative      4.000000
par(mar = c(10, 4, 4, 2))
barplot(sleepocqw$sleep_quality,
        names.arg = sleepocqw$occupation,
        col = coljack
,
        main = "Sleep quality based on Profession",
        axis.lty = 0,
        las=2,
        ylim = c(0,10),
        ylab = "Sleep quality (1-10)"
        
        )

sleepocst<-aggregate(stress_level ~ occupation, data = sleep, FUN = mean )
sleepocst<-sleepocst[order(-sleepocst$stress_level),]
print(sleepocst)
             occupation stress_level
7  Sales Representative     8.000000
8           Salesperson     7.000000
9             Scientist     7.000000
2                Doctor     6.732394
10    Software Engineer     6.000000
6                 Nurse     5.547945
4                Lawyer     5.063830
5               Manager     5.000000
1            Accountant     4.594595
11              Teacher     4.525000
3              Engineer     3.888889
bpst<-barplot(sleepocst$stress_level, 
              
              col = coljack,
              main = "Occupation and stress level",
              ylab = "Stress level (1-10)",
               ylim = c(0,10),
              
              )



text(
  x = bpst,
  y = sleepocst$stress_level + 0.3,
  labels = sleepocdu$occupation,
  srt = 90,      
  adj = 0,
  cex = 1
)

table(sleep$sleep_disorder)

   Insomnia        None Sleep Apnea 
         77         219          78 

Sleep Apnea is most common (excluding no illness)