HW2_skeleton

Section 2.1

7

1. type answer here.

OF

2. type answer here.

15

3. type answer here.

15

4. type answer here.

The graph does not distinct the three outfield positions and makes it seems to have much more OFs than the others, which makes the award seem unfair.

9

1. type answer here.

70%

2. type answer here.

22% * 240 million = 52.8 million.

3. type answer here.

It’s inferential, because it’s a claim based on samples.

11

1. type answer here.

The proportion of 18-to-34-year-old respondents who are more likely to buy is 43%. The proportion of 35-to-44-year-old respondents who are more likely to buy is 61%.

2. type answer here.

The group of age 55+ are more likely to buy when made in America.

3. type answer here.

The group of age between 18 and 34.

4. type answer here.

There is a positive association between age and likelihood to buy, that is older people are more likely to buy when made in America.

13

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

rel.freqq <- datt/sum(datt)

categoriess <- c("Never", "Rarely", "Sometimes", "Most of time", "Always")


answerr <- data.frame(categoriess,rel.freqq)

answerr

##    categoriess  rel.freqq
## 1        Never 0.02617253
## 2       Rarely 0.06783920
## 3    Sometimes 0.11557789
## 4 Most of time 0.26319095
## 5       Always 0.52721943

2. type answer here.

percentage of ansering “always” = 2518/(125+324+552+1257+2518) = 52.72%

3. type answer here.

Percentage of ansering “never” or “Rarely” = (125+324)/(125+324+552+1257+2518) = 9.40%

barplot(datt,main="Seat Belt Usage",names=categoriess, col =c("red","blue","green","yellow","orange"))

barplot(rel.freqq,main="Seat Belt Usage",names=categoriess, col =c("red","blue","green","yellow","orange"))

pie(datt,main="Seat Belt Usage",labels=categoriess, col =c("red","blue","green","yellow","orange"))

7. type answer here.

It’s inferential because the Centers for Disease Control gets that claim by deducing from samples.

15

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

rel.freq <- dat/sum(dat)

categories <- c("More 1", "Up to 1", "Few a week", "Few a month", "Never")


answer <- data.frame(categories,rel.freq)

answer

##    categories   rel.freq
## 1      More 1 0.36780488
## 2     Up to 1 0.18731707
## 3  Few a week 0.12878049
## 4 Few a month 0.07902439
## 5       Never 0.23707317

2. type answer here.

Proportion of those who never use the Internet = 243/1025 = 23.71%

barplot(dat,main="Internet Usage",names=categories, col =c("red","blue","green","yellow","orange"))

barplot(rel.freq,main="Internet Usage(Relative Freq)",names=categories, col =c("red","blue","green","yellow","orange"))

pie(dat,main="Internet Usage",labels=categories, col =c("red","blue","green","yellow","orange"))

6. type answer here.

This statement is wrong because 1025 people are too few to represent all adult Americans.

Section 2.2

9

1. type answer here.

it’s 8

2. type answer here.

it’s 2

3. type answer here.

it’s 15

4. type answer here.

it’s 4

5. type answer here.

it’s 15/100=15%

6. type answer here.

The distribution is symmetric.

10

1. type answer here.

it’s 4

2. type answer here.

9 weeks

3. type answer here.

percentage of time 2 cars were sold = 9/(4+2+9+8+12+8+5+2+1+0+1) =17.31%

4. type answer here.

This distribution is right skewed.

11

1. type answer here.

sample=2+3+13+42+58+40+31+8+2+1=200

2. type answer here.

class width= (160-60)/10=10

3. type answer here.

class of 60-70 with a frequency of 2 class of 70-80 with a frequency of 3 class of 80-90 with a frequency of 13 class of 90-100 with a frequency of 42 class of 100-110 with a frequency of 58 class of 110-120 with a frequency of 40 class of 120-130 with a frequency of 31 class of 130-140 with a frequency of 8 class of 140-150 with a frequency of 2 class of 150-160 with a frequency of 1

4. type answer here.

the class of 100-110

5. type answer here.

The class of 150-160

6. type answer here.

Percentage of students with an IQ of at least 130 = (8+2+1)/200 = 5.5%

7. type answer here.

No.

12

1. type answer here.

class width = 200-0=200

2. type answer here.

class of 0-200 class of 200-400 class of 400-600 class of 600-800 class of 800-1000 class of 1000-1200 class of 1200-1400

3. type answer here.

the class of 0-200

4. type answer here.

The distribution is right skewed.

5. type answer here.

The reporter cannot conclude causal relationship from observation studies.

13

1. type answer here.

It should be bell-shaped, because comparied with the majority of households, there are very few households that earn a very large amount of money or very little money.

2. type answer here.

It should be left skewed, because the majority students taking SAT have high scores, and it’s very hard to have extremely low score in SAT exams.

3. type answer here.

It should be right skewed because very large families are rare.

4. type answer here. It should be left skewed, because young people are less likely to be diagnosed with Alzheimer’s disease.

14

1. type answer here.

It should be right skewed because the majority of people would not drink too much, and it’s impossible to have a negative number of drinks.

2. type answer here.

It should be bell-shaped, because students are usually at similar ages like 18, 19, 20, and 21.

3. type answer here.

It should be left skewed because older people are more likely to have hearing-aids.

4. type answer here.

It should be bell-shaped, because people who are extremely tall or extremely short are really rare.