2.1 7-15 odds

    1. China

  1. 50

  2. 360

  3. It does not take into account the population of each country. China has the largest population out of the other countries listed, hence why it’d have the most internet users.

    1. 0.44; 0.61

  1. 55+

  2. 18-34

  3. The older the population gets, the more likely they’ll buy when made in America.

    1. Never 0.026; Rarely 0.067; Sometimes 0.11; Most of the time 0.26; Always 0.52

  1. 52.1%

  2. 9.4%

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

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

barplot(my_data, main = "Frequency Bar Chart", names.arg = groups, col = c("purple", "blue", "yellow", "green", "red"))

my_data <- c(0.026, 0.068, 0.116, 0.263, 0.527)

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

barplot(my_data, main = "Relative Frequency Bar Chart", names.arg = groups, col = c("purple", "blue", "yellow", "green", "red"))

my_data <- c(0.026, 0.068, 0.116, 0.263, 0.527)

groups <- c("Never 2.6%", "Rarely 6.8%", "Sometimes 11.6%", "Mostly 26.3%", "Always 52.7%")

pie(my_data, labels = groups, main = "Pie Chart", col = c("purple", "blue", "yellow", "green", "red"))

  1. Inferential
    1. More than 1 hour a day 0.37; Up to 1 hour a day 0.19; A few times a week .12; A few times a month or less .08; Never 0.24

  1. 0.24/24%

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

groups <- c("1 hour+", "1 hour-", "Weekly", "Monthly-", "Never")

barplot(my_data, main = "Frequency Bar Chart", names.arg = groups, col = c("purple", "blue", "yellow", "green", "red"))

my_data <- c(0.37, 0.19, 0.12, 0.08, 0.24)

groups <- c("1 hour+", "1 hour-", "Weekly", "Monthly-", "Never")

barplot(my_data, main = "Relative Frequency Bar Chart", names.arg = groups, col = c("purple", "blue", "yellow", "green", "red"))

my_data <- c(0.37, 0.19, 0.12, 0.08, 0.24)

groups <- c("1 hour+ 37%", "1 hour- 19%", "Weekly 12%", "Monthly- 8%", "Never 24%")

pie(my_data, labels = groups, main = "Pie Chart", col = c("purple", "blue", "yellow", "green", "red"))

  1. No confidence in the statement.

2.2 9-16

    1. 8

  1. 2

  2. 15

  3. 4

  4. 15%

  5. Bell shaped

    1. 4

  1. 9 weeks

  2. 17%

  3. Skewed Right

    1. 200

  1. 10

  2. 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

  3. 100-109

  4. 150-159

  5. 5.5%

  6. No

    1. 51

  1. 0-199; 200-399; 400-599; 1000-1999; 14000-1599

  2. 0-199

  3. Skewed Right

  4. The quality of the road has nothing to do with alcohol-related deaths. A fair comparison can be made if one includes age and population and ties it to something relevant.

    1. Skewed Right; a vast majority of the American population is in the lower income portion

  1. Bell-shaped; many students don’t do either terrible or extremely well, they’re in between

  2. Skewed Right; many households will consist of several house members, and fewer will consist of larger households

  3. Skewed Left; older age groups are the ones who mostlikely will be diagnosed with the disease

    1. Skewed Right; more population consumes a couple throughout the week, though usually during the weekend, only alcoholics will have an unsual/large amount

  1. Skewed Right; students as they begin to attend school are usually enrolled in public schools, as they age they might switch to private

  2. Skewed Left; it is common for older people to need hearing aid, there are only a few cases where young people will need it

  3. Bell-shaped; there is more of an average height common in full-grown men, only a few are smaller or taller

    1. 0 - 0.32; 1 - 0.36; 2 - 0.24; 3 - 0.06; 4 - 0.02

  1. 24%

  2. 60%

    1. 1 - 0.32; 2 - 0.22; 3 - 0.18; 4 - 0.14; 5 - 0.04; 6 - 0.06; 7 - 0; 8 - 0.02; 9 - 0; 10 - 0.02

  1. 0%

  2. 2%

  3. 14%