3.4

5

  1. -0.30, -0.43

  2. The 40 week gestation weighs less relative to the gestation period

7 The man is relatively taller

9 Hernandez had the better year because his ERA was 2.14 standard deviations which is below the American League mean but Johnsosn’s ERA was only 1.78 standard deviations which is below the National League’s mean ERA.

11 Will Power has more convincing victory since his finishing time was 1.76 standard deviations belows the mean. But, Franchitti’s vicotry was 1.48 standard deviations below the mean.

13 239

15 a. 15% of 3 to 5 month old males have a head circumference that is 41cm or less. 85% of 3 to 5 month old males have a head circumference that is greater than 41cm.

  1. 90% of 2 year old females have a waist circumference that is 52.7cm or less. 10% of 2 year old females havwe a waist circumference that is more than 52.7cm.

c.As the age increases the heights at each percentile decrease which means that male adults are getting taller

22 a. -1.21

  1. Q1=9.15, Q2=9.95, Q3=11.1

  2. IQR=1.95

  3. 5.7 is an outlier.

25 The cutoff point is 578 mintues

3.5

3 a. Skewed right

  1. 0,1,3,6,16

4 a. Symmetric

  1. -1, 2, 5, 8, 11

5 a. 40

  1. 52

  2. y, the box is wider than x.

  3. Symmetric becasue the box is in the middle part.

  4. Right skewed because the box is more toward the left.

6 a. 16

  1. 30

  2. y because its box is relatively larger and cotains more numbers than x does.

  3. yes, 30

  4. left-skewed, box is on the right.

7

your_data <- c(60, 68, 77, 89, 98)

boxplot(your_data, horizontal = T)

fivenum(your_data)
## [1] 60 68 77 89 98

8

your_data <- c(110, 140, 157, 173, 205)

boxplot(your_data, horizontal = T)

fivenum(your_data)
## [1] 110 140 157 173 205

9

your_data <- c(42, 47, 50, 52, 54, 55, 57, 61, 64, 43, 48, 51, 52, 54, 56, 57, 61, 65, 46, 49, 51, 54, 55, 56, 57, 61, 68, 46, 49, 51, 54, 55, 56, 58, 62, 69, 47, 50, 51, 54, 55, 57, 60, 64)

fivenum(your_data)
## [1] 42.0 50.5 54.5 57.5 69.0
boxplot(your_data, horizontal = T)

the shape of the data is pretty bell-shaped with an outlier.

10

your_data <- c(7.2, 7.8, 7.8, 7.9, 8.1, 8.3,
              8.5, 8.6, 8.6, 8.6, 8.7, 8.8,
              9.0, 9.1, 9.2, 9.2, 9.2, 9.4,
              9.4, 9.6, 9.7, 9.7, 9.9, 9.9,
              10.0, 10.0, 10.0, 10.1, 10.2,10.3,
              10.3, 10.3, 10.3, 10.7, 10.7, 10.9,
              11.2, 11.2, 11.2, 11.3, 11.3, 11.3,
              11.5, 11.5, 11.7, 12.4, 12.5, 13.6,
              13.8, 14.4, 16.4)


fivenum(your_data)
## [1]  7.20  9.05 10.00 11.20 16.40
boxplot(your_data, horizontal = T)

the shape of the data : right-skewed with an outlier.