2.1

7

  1. China

  2. 50 million

  3. 350 million

  4. Should use relative frequency since the population is different in different country. It is possible for a country to have a higher frequency because of a larger population.

9

  1. 69%

  2. 55.2 million

  3. Inferential, because it takes the sample of this survey to the entire population of adult Americans, and measure the reliability of the result.

11

  1. 0.42, 0.61

  2. 55+

  3. 18-34

  4. As age increases, the likelihood to buy when made in America increases.

13

Never: 0.0262

Rarely: 0.0678

Sometimes: 0.1156

Most of the time: 0.2632

Always: 0.5272

  1. 52.7%

  2. 2.6% + 6.8% = 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, because it takes the result from the sample extend it to the population of all college student.

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. 0.2371

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. Because it did not state where they acquired the information, it is not trustworthy.

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. 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. 55%

  7. No.

12

  1. 200

  2. Skip this problem

  3. 0-199

  4. Skewed Right

  5. They should use relative frequency since Texas has a higher population than Vermont, which means more drivers in Texas that has higher frequency

13

  1. Probably Skewed Right, because there are more people earning a lower income, and fewer people earning the high income.

  2. Probably Bell Shaped, scores often have a stonger middle portion, then the two sides are almost equally divided.

  3. Probably Skewed Right, because most of the household will have 2-5 people, there are fewer household that has more people.

  4. Probably Skewed Left, because old people are more likely to be diagnosed with Alzheimer’s disease, therefore there are fewer younger people be diagnosed.

14

  1. Probably Bell Shaped, the majority would consume an certain amount of alchol in the middle, then others either fewer or more tailing to both sides.

  2. Probably Uniform, there should me the same amount of students in each grade that are the same age.

  3. Probably Skewed Left, because the older age group are more likely need hearing-aid. the younger age group are almost not likely to have hearing-aid.

  4. Probably Bell Shaped, because the majority of men would likely have a height be average and in the middle, the rest are almost equally tailing to both sides.