Section 2.1

9

  1. 69%

  2. 55.2 million americans

  3. Inferential.

11

  1. .42, .61

  2. 55+

  3. 18-34

  4. The older one is, the more likely the are to buy the product that’s made in america.

13

  1. Response Frequency Relative Frequency Never 125 .02617 Rarely 324 .06784 Sometimes 552 .11558 Most of the Time 1257 .26319 Always 2518 .52722
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. 52.7%

  2. 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. Descriptive.

15

  1. Response Frequency Relative Frequency More than 1hr a day 377 .3678 Up to 1hr a day 192 .1873 Few times a week 132 .1288 Few times a month or less 81 .0790 Never 243 .2371
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. 23.7% or .2371

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

9

  1. 8

  2. 2

  3. 15 times.

  4. 4

  5. 15%

  6. bell shaped

10

  1. 4

  2. 9 weeks.

  3. 17.3%

  4. Bell shaped.

11

  1. 200

  2. 10

  3. 60-69 with frequency of 2, 70-79 with frequency of 3, 80-80 with frequency of 13, 90-99 with frequency of 42, 100-109 with frequency of 58, 110-119 with frequency of 40, 120-129 with frequency of 31, 130-139 with frequency of 8, 140-149 with frequency of 2, 150-159 with frequency of 1.

  4. 100-109

  5. 150-159

  6. 5.5%

  7. No.

12

  1. 200

  2. 0-199, 200-399, 400-599, 600-799, 800-999, 1000-1199, 1200-1399

  3. 0-199.

  4. skewed right.

13

  1. Skewed Right, because there are fewer people with high incomes.

  2. Bell Shaped. Most students will most likely score in the middle, not super high or super low.

  3. Skewed right. As the number of occupants in households increase, the frequency will likely go down.

  4. Skewed left. Alzheimer’s is a disease that is more prevalent in older people.

14

  1. Skewed right. The amount of alcoholic drinks per week will decrease as the amount getws larger.

  2. Potentially uniform. Students from grades k-12 that are in the public school system tend to stay in the public school system as they grow.

  3. Skewed left. Patients who use hearing aids tend to be on the older side.

  4. Bell shaped. The average height of a full grown man is around 5 ft 10 inches, but the heights surrounding this height are probably common as well.

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

num. children under 5 num households relative freq. 0 16 .32 1 18 .36 2 12 .24 3 3 .06 4 1 .02

  1. 24%

  2. 60%