2.1

7

  1. China

  2. 50 million

  3. 350 million

  4. China has a higher population, so it makes comparisons using frequencies and not relative frequencies difficult or misleading.

9

  1. 69%

  2. 55.2 million

  3. The statement is inferential, because the 8% was taken from a sample and not the whole population. So it was an assumption.

11

  1. 0.42; 0.61

  2. 55+

  3. 18-34

  4. As age increases, so does the likelihood to buy American products.

13

Never: 0.0262

Rarely: 0.0678

Sometimes: 0.1156

Most of the time: 0.2632

Always: 0.5272

  1. 52.7%

  2. 9.4%

d e f

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

groups <- c("Never", "Rarely", "Sometimes", "Most", "Always")

barplot(my_data, main = "Wearing Seatbelts", names.arg = groups)

barplot(my_data, main = "Wearing Seatbelts", names.arg = groups, col = c("red","blue","green","yellow", "black"))

rel_freq <- my_data / sum(my_data)

barplot(rel_freq, main = "Wearing Seatbelts", names.arg = groups, col = c("red","blue","green","yellow","black"))

pie(my_data, labels = groups, main = "Wearing Seatbelts")

  1. Inferential

15

More then 1 hour: 0.3678

Up to 1 hour: 0.1873

A few time a week: 0.1288

A few times a month: 0.0790

Never: 0.2371

  1. 23.7%

c d e

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

groups <- c("More 1", "Up to 1", "Few times week", "Few times month", "Never")

barplot(my_data, main = "Use the internet", names.arg = groups)

barplot(my_data, main = "Use the internet", names.arg = groups, col = c("red","blue","green","yellow", "black"))

rel_freq <- my_data / sum(my_data)

barplot(rel_freq, main = "Use the internet", names.arg = groups, col = c("red","blue","green","yellow","black"))

pie(my_data, labels = groups, main = "Use the internet")

  1. There are no credentials to provide credence to the estimate.

2.2

9

  1. 8

  2. 2

  3. 15

  4. 4

  5. 15%

  6. Bell shaped

10

  1. 4

  2. 9

  3. 16.98%

  4. Skewed right

11

  1. 200

  2. 10

  3. 60-69,2; 70-79,3; 80-89,13; 90-99,42; 100-109,58; 110-119,40; 120-129,31; 130-139,8; 140-149,2; 150-159,1

  4. 100-109

  5. 150-159

  6. 5.5%

  7. No

12

  1. 200

  2. Skip this problem

  3. 0-199

  4. skewed right

  5. The wording doesn’t paint a clear picture and take account of all factors. The roads in Vermont could be a lot less safer than Texas because of snow related accidents and other types of accident. The only comparison that can be made with the data given is alcohol related traffic deaths only. 13

  6. Skewed right, because most household hold incomes will be to the left with a few higher incomes to the right

  7. Bell shaped, because most scores will probably occur near the middle with higher and lower scores tapering off on both sides

  8. Skewed right, because most households will have a lower number of occupants, while a few will have a higher number of occupants

  9. Skewed left. Alzheimer’s patients tend to be an older age, with few patients being younger.

14

  1. Skewed right, most (stable and responsible) people drink few drinks during the week, while there are the special few who drink a lot during the week.

  2. Uniform. There is a about even mix of kids around the same age in public school.

  3. Skewed right.The average age of people who near hearing aids are mainly the elderly.

  4. Bell shaped. Typically, full grown men are around 5-6 feet, with a couple being smaller and larger than that.