1.1

1. Statistics is the logic of uncertainty. It is the science of collecting, organizing and summarizing, and analyzing information to draw conclusions about a question.

3. An individual is a person or object that is a memner of the population being studied.

5. A statistic is the numerical summary of a sample.

7. Parameter

9. Parameter

11. Statistic

13. Parameter

15. Qualitative

17. Quantitative

19. Quantitative

21. Qualitative

23. Discrete

25. Continuous

27. Continuous

29. Discrete

39 Population: all teenagers ages 13-17; Sample: 1028 teens ages 13-17 surveyed

40 Population: total bottles of Coca-Cola filled on Oct. 15; Sample: 50 randomly selected bottles filled on Oct. 15

41 Population: all soybean plants on farm; Sample: 100 randomly selected plants

42 Population: all households within the US; Sample: 50,000 households surveyed

1.2

11. Experiment

13. Observation

2.1

7

  1. China

  2. ~50 million

  3. ~350 million

  4. Each country has a different population of possible internet users.

9

  1. ~68%

  2. ~22% or 52.8 million

  3. Descriptive; Gallup observed that 8% of the population believes this

11

  1. 44%; 61%

  2. ages 55+

  3. ages 18-34

  4. The older the person, the more likely he/she is going to buy a good made in America

13

  1. Never: 0.026 Rarely: 0.068 Sometimes: 0.116 Most of the time: 0.263 Always: 0.527

  2. 52.7%

  3. 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; an experiment was conducted, and an inference was drawn

15

More then 1 hour: 0.368

Up to 1 hour: 0.187

A few time a week: 0.129

A few times a month: 0.079

Never: 0.237

  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. The data shows that 37% of 1,025 Americans surveyed answered that - not necessarily all adult Americans.

2.2

9

  1. 8

  2. 2

  3. 15 times

  4. 4 more times

  5. 15%

  6. symmetric; bell-shaped

10

  1. 4 cars

  2. 9 weeks

  3. 17.3%

  4. skewed-right

11

  1. 200 students sampled

  2. 10

  3. class: 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% of students

  7. No

12

  1. 200

  2. 0-200

  3. right-skewed

  4. population sizes differ between states; compare the relative frequency for accuracy

13

  1. Right-skewed: there is a barrier to the minimum income a household can earn ($0), but there is no such barrier on the maxmimum possible income. Most households will earn an income relatively closer to 0; there are more households earning a higher-than-average income than there are earning a lower-than-average income.

  2. Bell-shaped: generally, most people will score around the median score. There will be just as many people scoring below the average as there will be scoring above the average.

  3. Right-skewed: similar to income there is a barrier to the minimum number of people in a household (1 person), but there is technically no such barrier on the other end of the spectrum. So there is a greater possibility to have a more-than-average number of people in a household than there is to have a less-than-average number of people.

  4. Left-skewed: the average age of patients diagnosed with Alzheimer’s disease will be within a much older age group. Since there is a barrier on either end of the spectrum, we can assume that there will be smaller chance that people are diagnosed with Alzheimer’s above the average age of diagnosis than there will be below.

14

  1. Bell-shaped: there is most likely an equal probability of people consuming more and less than the average number of alcoholic beverages per week.

  2. Uniform: unless there is a baby-boom, there will likely be the same number of students at each age within a public school district.

  3. Left-skewed: the average age of hearing-aid patients will be within a much older age group. So there is a greater possibility of a person being a hearing aid patient below the average age than there is of a person above the average age.

  4. Bell-shaped: there will be an equal possibility of full-grown men being taller than the average height as there will be men shorter than the average height.