2.1

7

  1. China

  2. 50 million

  3. 350 million

  4. This graph should use relative frequencies, rather than frequencies.

9

  1. 69%

  2. 55.2 million

  3. Inferential, since it is a generalization based on the observed data. It takes a result from a sample and extend it to the populaiton.

11

  1. 0.42; 0.61

  2. 55+ age group

  3. 18-34 age group

  4. As the age increases, people tend to buy things made in America more likely

13

Never: 0.0262

Rarely: 0.678

Sometimes: 0.1156

Most of the time: 0.2632

Always: 0.5272

  1. 52.72%

  2. 70.42%

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, since it is based on the results of a sample survey, and then extends to the population.

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. It provides an estimate, but no level of confidence is given.

2.2

9

  1. 8

  2. 2

  3. 15

  4. 4

  5. 15%

  6. Bell shaped

10

  1. 4 cars

  2. 9 weeks

  3. 17.31%

  4. Slightly skewed to the right

11

  1. 200

  2. 10

  3. Class(IQ) Frequency 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 to the right

  5. The statement is wrong because of the different size of population. The reporter can make a comparison between the number of fatalities per 100 residents from these two places.

13

a.Skewed right. Most household incomes will be to the left, and fewer higher incomes to the right.

  1. Bell-shaped. The scores that most students get will in the middle range, and fewer students get scores in both the left and the right.

  2. Skewed right. Most households holds less than 5 people, and fewer households holds higher number of people.

  3. Skewed left. Most Alzheimer’ s patients tend to fall into the old-age categories, and fewer young patients on the left.

14

  1. Skewed right. More people consume fewer alcoholic drinks per week, and less people consume more per week.
  1. Likelybell-shaped.Mostheightswill occur, say, in the 66- to 70-inch range, with heights tapering off equally in both directions.

  1. Uniform, since there are equal number of students in each age category.

  2. Skewed left, most hearing-aid patients tend to be old, while fewer young hearing-aid patients.

  3. Bell-shaped. Most full-grown men have a height from 65-75 inches, while fewer men with height less than 65 inches and more than 75 inches.