Reading 2.1, problems => 7 - 15 odd

  1. a.China

b.50 millions

c.350 millions

d.It doesn’t provide readers a relative frequency graph, in order to make sure the numbers of oberservation in each category are the same.

9.a.69 percent

b.about 55.2 millions

c.Inferential; people showed on the bar graph didn’t make a clear viewpoint in his survey, so Gallup deduct from the result that those people think divorce is acceptable in certain situation.

11.a.0.43/0.61

b.55+

c.18-34

d.The tendency to be more likely to buy a product when is “made in America”" increases when the age of people increases;on the other hand, People’s tendency to be less likely to buy decreases from old to young people.

13.a. never 0.0262

  rarely  0.0678

  sometimes 0.1156

  most of time 0.2632

  always 0.5272

b.52.72%

c.9.4%

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

groups <- c("never", "rarely", "sometimes", "most of time", "Always")

barplot(my_data, cex.names = 0.6, main = "How often do you wear a seat belt?", names.arg = groups, col = c("red","blue","green","yellow", "purple"))

e.

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

groups <- c("never", "rarely", "sometimes", "most of time", "Always")


rel_freq <- my_data / sum(my_data)

barplot(rel_freq, cex.names = 0.6, main = "How often do you wear a seat belt?", names.arg = groups, col = c("red","blue","green","yellow", "purple"))

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

groups <- c("never", "rarely", "sometimes", "most of time", "Always")

pie(my_data, labels = groups, main = "How often do you wear a seat belt?", col = c("red","blue","green","yellow", "purple"))

g.descriptive

15.a. More than 1 hour a day 0.3678

  Up to 1 hour a day 0.1873

  A few times a week 0.1288

  A few times a month or less 0.0790

  Never 0.2371

b.0.2371

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

groups <- c("More than 1 hour a day", "Up to 1 hour a day", "A few times a week", "A few times a month or less", "Never")

barplot(my_data, cex.names = 0.6, main = "How much time do you spend using the Internet", names.arg = groups, col = c("red","blue","green","yellow", "purple"))

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

groups <- c("More than 1 hour a day", "Up to 1 hour a day", "A few times a week", "A few times a month or less", "Never")

rel_freq <- my_data / sum(my_data)

barplot(rel_freq, cex.names = 0.6 , main = "How much time do you spend using the Internet", names.arg = groups, col = c("red","blue","green","yellow", "purple"))

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

groups <- c("More than 1 hour a day", "Up to 1 hour a day", "A few times a week", "A few times a month or less", "Never")

pie(my_data, labels = groups, main = "How much time do you spend using the Internet", col = c("red","blue","green","yellow", "purple"))

f.Because it underestimated the number of people, both groups “A few times a week” and “A few times a month or less” could use more than 1 hour one day, thus the statement is wrong.

Reading 2.2, problems => 9 - 14

9.a.8

b.2

c.15

d.4

e.15%

f.Bell-shaped

10.a.4

b.2

c.7.69%

d.Bell-shaped

11.a. 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

d.100~109

e.150~159

f.5.5%

g.None

  1. a.200

    1. 0~199 26

    200~399 14

    400~599 8

    600~799 0

    800~999 0

    1000~1199 3

    1200~1399 0

    1400~1599 1

c.0~199

d.Skewed Right

e.The statement is wrong because the reporter compares two different objects.In comparasion between alcohol-related traffic fatalities in Texas versus Vermont, the report compared the frequency of fatalities versus the number of fatalities by state, so the statement is wrong.

13.a.Skewed right. Most of households seldom have high incomes, and households usually have incomes in a lower range.

b.Bell-shaped. People get most scores on a standardized exam at the middle like 2000 in SAT, and others have scores that distrubute in higher or lower range.

c.Skewed right. People usually live in household when they do not have stable income sources or too young to live along, and people will leave the household as their ages increase.

d.Skewed left. The Alzheimer’s diseases usually occur in middle or old age, and the possibilities of getting diseases increase as the the ages of patients increase.

14.a.Skewed right. The comsumption od drink will decrease with time, because people’s drinking capability decreased.

b.Uniform. Students usually have the same ages in one grade in the public school.

c.Skewed left. The possibilities of using hearing-aid increases with people’s ages increase.

d.Bell-shaped. Most full-grown men have heights in certain middle range, and rest of them might be taller or shorter.

Strategic Practice

Constructing a histogram of the “dist” variable from the “cars” data set.

It’s bell-shaped.

cars[1:10,]
##    speed dist
## 1      4    2
## 2      4   10
## 3      7    4
## 4      7   22
## 5      8   16
## 6      9   10
## 7     10   18
## 8     10   26
## 9     10   34
## 10    11   17
hist(iris$Sepal.Length)