CH.2.1 #7-15 odd

7 a) China

  1. 50 million

  2. approx. 350 million

  3. there seems to be a huge distance and are measured in frequency so the height is even greater.

9 a) 69%

  1. 55.2 million

  2. The statement is descriptive because it is taking a statistic from the sample data.

11 a) About 44% people between 18-34 years old are more likely to buy products made in America, while 61% of people between 35-44 are more likely to buy a product made in America

  1. 55+ have the greatest proportion of people who are more likely to buy a product made in America.

  2. The 18-34 year old age group has the largest amount of people who are less likely to buy a product because it was made in America

  3. The older the person, the more likely they are to support and buy American goods.

13 a) relative frequency distribution

Response = Relative Frequency

Never = .026

Rarely = .068

Sometimes = .116

Most of the time = .263

Always = .527

  1. 52.7%

  2. .1%

  3. frequency bar graph

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

groups <- c("never", "rarely", "sometimes", "most times", "always")


barplot(my_data, main = "College Survey", names.arg = groups, col = c("pink","cyan","green","yellow","orange"))

  1. relative frequency bar graph
my_data <- c(125, 324, 552, 1257, 2518)

groups <- c("never", "rarely", "sometimes", "most times", "always")

rel_freq <- my_data / sum(my_data)

barplot(rel_freq, main = "College Survey", names.arg = groups, col = c("pink","cyan","green","yellow","orange"))

  1. pie chart
my_data <- c(125, 324, 552, 1257, 2518)

groups <- c("never", "rarely", "sometimes", "most times", "always")

pie(my_data, labels = groups, main = "College Survey")

  1. descriptive

15 a) Response = Relative Frequency

More than 1 hour a day = .368

Up to 1 hour a day = .187

A few times a week = .129

A few times a month = .079

Never = .237

  1. 23.7%

  2. frequency bar graph

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

groups <- c(">1 hr daily", "up to 1 hour daily", "few times a wk", "a few times a month", "never")

barplot(my_data, main = "Use the Internet", names.arg = groups, col = c("pink","cyan","green","yellow","purple"))

  1. relative frequency bar graph
my_data <- c(377, 192, 132, 81, 243)

groups <- c(">1 hour daily", "up to 1 hour daily", "few times a wk", "few times a month", "never")

rel_freq <- my_data / sum(my_data)

barplot(rel_freq, main = "Use the Internet", names.arg = groups, col = c("pink","cyan","green","yellow","purple"))

  1. pie chart
my_data <- c(377, 192, 132, 81, 243)

groups <- c(">1 hour daily", "up to 1 hour daily", "few times a wk", "few times a month", "never")

pie(my_data, labels = groups, main = "Use the Internet")

  1. it is rounded and is not an approximate statement and this is a sample

Ch. 2.2 #9-16

9 a) 8

  1. 2

  2. 15 times

  3. 5 more 5’s were observed than 4’s

  4. 15% of the rolls were 7

  5. symettric bell-shaped curve

10 a) 4 cars

  1. 9 weeks

  2. .173 or 17.3% of the time.

  3. skewed right

11 a) 200 7th grade students were sampled

  1. class width= (160-60/10)= 154

  2. IQ scores = Frequency

    (60-70) = 2

    (70-80) = 3

    (80-90) = 13

    (90-100) = 42

    (100-110) = 58

    (110-120) = 40

    (120-130) = 31

    (130-140) = 8

    (140-150) = 2

    (150-160) = 1

  3. 7th grade students with an IQ between 100-110

  4. 7th grade students with an IQ between 150-160

  5. .05 or 5% of 7th grade students had an IQ of at least 130

  6. no

12 a) class width= (1600-0)/5 = 320

  1. fatalities by state = frequency (0-200) = 26

    (200-400) = 14

    (400-600) = 8

    (1000-1200) = 2

    (1400-1600) = 1

  2. the class of fatalities between (0-200)

  3. skewed right

  4. The reporter is using an inferential statement in that the are assuming that Vermont is much safer than Texas in Alcohol-Related Traffic Fatalities, but it could just be that Vermont has better rules for and more cops looking out for drunk drivers, r any other scenario, so we cannot assume that Vermont is safer.

13 a) skewed right as their are more poor than rich people in America

  1. bell shaped, all students fall in approximately the same score and others score above significantly higher or lower.

  2. bell-shaped because the average family is about 3 people so most family fall in that range or slightly above or below

  3. skewed left as older people are more likely to have alzheimer’s disease.

14 a) skewed left as we get closer to the end of the week, more drinks will likely be consumed over the weekend

  1. uniform. The age of middle schoolers will be close in age, so there won’t be much difference.

  2. skewed left. Hearing loss is more apparent and likely to happen the older you get

  3. bell shaped. Most men tend to all fall at the same average 5’5“-6’ and all the others tend to be above and below that.

15 a) # of children under 5 = relative frequency of households

0 = .32

1 = .36

2 = .24

3 = .06

4 = .02

  1. .24 or 24% of households have children under the age of 5

  2. .60 or 60% of households have children under the age of 5

16 a) # of Frees throwa until a miss = relative frequency

1 = .32

2 = .22

3 = .18

4 = .14

5 = .04

6 = .06

7 = 0

8 = .02

9 = 0

10 = .02

  1. .14 or 14% of the time she missed the 4th free throw

  2. .02 or 2% of the time she missed the 10th free throw

  3. .14 or 14% of the time she made at least 5 free throws