Section 2.1

2 type answer here number, proportion 3 type answer here The relative frequencies should add up to 1 5

  1. type answer here Washing your hands - 61%
  2. type answer here Drinking orange juice - 2%
  3. type answer here 25%

13

datt <- c(125, 324, 552, 1257, 2518)

rel.freqq <- datt/sum(datt)

categoriess <- c("Never", "Rarely", "Sometimes", "Most of time", "Always")


answerr <- data.frame(categoriess,rel.freqq)

answerr
##    categoriess  rel.freqq
## 1        Never 0.02617253
## 2       Rarely 0.06783920
## 3    Sometimes 0.11557789
## 4 Most of time 0.26319095
## 5       Always 0.52721943
  1. type answer here. 2518/4803= 52.7%
  2. type answer here. 449/4803=9.4%
barplot(datt,main="Seat Belt Usage",names=categoriess, col =c("red","blue","green","yellow","orange"))

barplot(rel.freqq,main="Seat Belt Usage",names=categoriess, col =c("red","blue","green","yellow","orange"))

pie(datt,main="Seat Belt Usage",labels=categoriess, col =c("red","blue","green","yellow","orange"))

  1. type answer here. Descriptive because it is reporting a result

15

dat <- c(377,192,132,81,243)

rel.freq <- dat/sum(dat)

categories <- c("More 1", "Up to 1", "Few a week", "Few a month", "Never")


answer <- data.frame(categories,rel.freq)

answer
##    categories   rel.freq
## 1      More 1 0.36780488
## 2     Up to 1 0.18731707
## 3  Few a week 0.12878049
## 4 Few a month 0.07902439
## 5       Never 0.23707317
  1. type answer here. 243/1025= .237= about 24%
barplot(dat,main="Internet Usage",names=categories, col =c("red","blue","green","yellow","orange"))

barplot(rel.freq,main="Internet Usage(Relative Freq)",names=categories, col =c("red","blue","green","yellow","orange"))

pie(dat,main="Internet Usage",labels=categories, col =c("red","blue","green","yellow","orange"))

Section 2.2

7 type answer here False. The shape of the distribution is skewed right. 8 type answer here True. 9 type answer here

  1. type answer here. 8
  2. type answer here. 2
  3. type answer here. 15
  4. type answer here. 4
  5. type answer here. 15/100=15%
  6. type answer here. Bell shaped

10

  1. type answer here. 4 cars
  2. type answer here. 9
  3. type answer here. 9/52 x 100% = 17.3%

  4. type answer here. Skewed right 13

  5. type answer here. Skewed right, lowest to highest income, fewer incomes to the right (millions)
  6. type answer here. Bell shaped. Students are going to be all over the spectrum, most occuring in the middle range, some with high scores and some with low scores too.
  7. type answer here. Skewed right. Most households will have more kids between 1-4, meaning higher number of children are less likely.

  8. type answer here. Most likely skewed left. The younger population would be less likely to get Alzheimer’s disease.

14

  1. type answer here. Skewed left, youngest to oldest. The younger people are not drinking but once 21 it is increased.
  2. type answer here. Skewed right, youngest to oldest. The younger students are going to be attending public schools rather than older people.
  3. type answer here. Skewed right, with the older population being more likely to be wearing hearing aids
  4. type answer here. Bell shaped. Most men are around the same height of 5’8“-5’11”, though some wiill be shorter and others will be taller.

15

dattt <- c(16, 18, 12, 3, 1)

rel.freqqq <- dattt/sum(dattt)

categoriesss <- c("Zero", "One", "Two", "Three", "Four")

answerrr <- data.frame(categoriesss,rel.freqqq)

answerrr
##   categoriesss rel.freqqq
## 1         Zero       0.32
## 2          One       0.36
## 3          Two       0.24
## 4        Three       0.06
## 5         Four       0.02
  1. type answer here. 24%
  2. type answer here. 60%

16

free_throws <- c(16, 11, 9, 7, 2,3,0,1,0,1)

rel.freqqq <- free_throws/sum(free_throws)

categoriesss <- c("1", "2", "3", "4","5","6","7","8","9","10")

answerrr <- data.frame(categoriesss,rel.freqqq)

answerrr
##    categoriesss rel.freqqq
## 1             1       0.32
## 2             2       0.22
## 3             3       0.18
## 4             4       0.14
## 5             5       0.04
## 6             6       0.06
## 7             7       0.00
## 8             8       0.02
## 9             9       0.00
## 10           10       0.02
  1. type answer here. 14%
  2. type answer here. 2%
  3. type answer here. 14%

25

  1. type answer here. Discrete. The number of televisions in the households are countable.
tv <- c(1, 1, 1, 2, 1,
        1, 2, 2, 3, 2,
        4, 2, 2, 2, 2,
        2, 4, 1, 2, 2,
        3, 1, 3, 1, 2,
        3, 1, 1, 2, 1,
        5, 0 ,1, 3, 3,
        1, 3, 3, 2, 1)

#table(tv)

tv <- c(1,14,14,8,2,1)

tv.freq <- tv/sum(tv)

tv.cat <- c("0", "1", "2", "3","4","5")

freq.tab <- data.frame(tv.cat,tv)
rfreq.tab <- data.frame(tv.cat,tv.freq)


freq.tab
##   tv.cat tv
## 1      0  1
## 2      1 14
## 3      2 14
## 4      3  8
## 5      4  2
## 6      5  1
rfreq.tab
##   tv.cat tv.freq
## 1      0   0.025
## 2      1   0.350
## 3      2   0.350
## 4      3   0.200
## 5      4   0.050
## 6      5   0.025
  1. Type answer here 20%
  2. Type answer here 7.5%