Section 2.1

7

  1. OF (outfielders)

  2. 15

  3. 15

  4. These positions are grouped together under the “outfield” position, when they should have their own category.

9

  1. about 69%

  2. 55,200,000 Americans

  3. It would be inferential, because the statistic is being applied to the sample.

11

  1. For 18-34 year olds the proportion is .42 and the proportion for 35-44 year old is .62

  2. 55+ group

  3. 18-34 group

  4. It is apparent that as age increases, so does the likelihood for wanting to purchase US made goods.

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

  1. 53%

  2. 9.4%

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"))

  1. This is a descriptive statistic, because it is a numerical summary of the sample.

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

  1. .24

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"))

  1. They are applying a statistic from the sample to a population that was not polled.

Section 2.2

9

  1. 8

  2. 2

  3. 15 times

  4. 4 more 5’s

  5. 15%

  6. The distribution is a bell curve

10

  1. 4

  2. 9

  3. 17.3%

  4. The distribution is right skewed

11

  1. 200

  2. 10

  3. 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, 150-160=1

  4. 100-109

  5. 150-159

  6. 5.5%

  7. no

12

  1. 200

  2. 0-199, 200-399, 400-599, 600-799, 800-999, 1000-1199, 1200-1399

  3. 0-199

  4. The distribution is right skewed

  5. Vermont is much smaller that Texas and the data was not adjusted to account for differences in population size.

13

  1. right skewed, there will likely be more people with lower and moderately high incomes, than with excessively large incomes.

  2. bell curve, because the test is standarized it is likely that individuals will score in the middle range with less people scoring very high or very low.

  3. right skewed, there will likely be more households with smaller numbers of indivuals than household with large numbers of individuals.

  4. left skewed, individuals diagnosed with Alzheimer’s will generally be much older and frequencies will increase as age increases.

14

  1. right skewed, there would likely be more people who consume a small amount of drinks than heavy drinkers.

  2. uniform, it is likely that there is an even amount of students in each grade level.

  3. left skewed, there would be an increase in the need for hearing aides as age increases.

  4. bell curve, height would likely be centered in the middle around the average height for a full grown man.