1.1

1. Statistics is the feild that analyzes information in a mathematical way in order to present this information in a way that can be worked with and from which conclusions with power can be drawn.

3. An INDIVIDUAL is a person/object that is a member of the population being studied.

5. A STATISTIC is a numerical summary of a sample.

7. Parameter

9. Statistic

11. Parameter

13. Statistic

15. Qualitative

17. Quantitative

19. Qualitative

21. Qualitative

23. Discreet

25. Continuous

27. Continuous

29. Discreet

39 The population is all of the teens aged 13-17 in the US, while the Sample was the 1028 teens asked.

40 The population is all of the coca-cola bottles processed on October 15, and the sample is the 50 randomly selected bottles.

41 The population is the entire soybean crop, and the sample is the 100 soybean plants weighted.

42 The population is all of the US households, and the sample is the 50,000 households contacted.

1.2

11. Experiment

13. Observational study

2.1

7

  1. China

  2. 50 million

  3. about 365 million

  4. This may be misleading because the graph shows the total number of internet users rather than the number of users proportional to the total population of that country.

9

  1. about 69%

  2. about 55.2 million

  3. I would say that that statement is inferencial, because the actual answer provided was ‘depends on situation’ rather than ‘is acceptable in certain situations’. Of course, that is what ‘depends on situation’ probably means, but that is what inference means.

11

  1. 45% =18-34, 61%=35-44

  2. the 55+ age group

  3. 18-34 age group

  4. The apparent association is that the older the adult age group is, the more likely that the age gourp would buy somehting made in America.

13

Never: 2.6%

Rarely: 6.8%

Sometimes: 11.6%

Most of the time: 26.3%

Always: 52.7%

  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. That is a descriptive statement

15

More then 1 hour: 36.8%

Up to 1 hour: 18.7%

A few time a week: 12.9%

A few times a month: 7.9%

Never: 23.7%

  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. They rounded up from 36.8%, and with a group as big as the entire adult population of the US, that 0.02% makes a pretty big difference.

2.2

9

  1. 8

  2. 2

  3. 15

  4. 4

  5. 15%

  6. Slightly right skewed.

10

  1. 4

  2. 9

  3. 17.3%

  4. slightly left skewed

11

  1. 200

  2. 10

  3. 60-70=1%, 70-80=1.5% , 80-90=6.5%, 90-100=21% , 100-110=29% , 110-120= 20%, 120-130=15.5% , 130-140=4% , 140-150=1% , 150-160= 0.5%

  4. 100-110

  5. 150-160

  6. 5.5%

  7. no

12

  1. 200

  2. Skip this problem

  3. 0-200

  4. left skewed

  5. That statement is not entirely accurate mostly due to the large difference in size between Vermont and Texas, and partially due to other factors, such as (potentially) population density, the popularity of alcohol, and the conditions of the roads.

13

  1. I would expect the average household income in the US to be left skewed because I think that there are many people living in poverty in the US, and many people living in poor economic conditions higher than poverty. There are also relatively few millionares and billionares.

  2. I would expect the SAT exam to be Bell shaped and uniform because the test is designed so that the majority of people who take it fall somewhere in the middle.

  3. I would expect the number of people living in a household to be more or less bell shaped, perhaps with a slight skew to the left. This is because in this day and age few people can afford to live alone when they are young adults, and children and older adults usully live in family households. Family sizes in the US are generally 3-5 people in size, with some exceptions. There are also people who can afford to live alone, and I am unsure as to how many.

  4. I would expect this to be right skewed because Alzheimer’s disease is generally diagnosed in people over the age of 65 (the WHO states that in western nations the age of 65 and older is generally accepted as the definition of elderly). Diagnosis of Alzheimer’s in people younger than that is rare.

14

  1. There is not enough information present to answer this question well. It neither states the population being studied, nor did it give a clear definition of the time parameters. For example, if it was college students and days of the week, then I would expect the amount to peak on Friday and Saturday. If it was of middle aged adults, and it was over the course of a year, I would expect it to peak around holidays such as Christmas, New Years, and the Fourth or July.

  2. I would expect this histogram to be relatively uniform as there are supposed to be about the same number of students in each grade.

  3. I would expect this histogram to be very much right skewed for more or less the same reason as I gave for Alzheimer’s. While there are people with hearing aides who are not elderly, a lifetime of ear drum damage eventually makes an impact on most people, and many elderly people wither have hearing aides, or should have hearing aides.

  4. I would expect this to be bell shaped, as the majority of men (in the US) are somewhere between 5’5" and 6’5“. There are defenately people outside of those heights, but I would say that the majority fall in that category.