3.4

5 -.30, -.43, the 40 week gestation baby.

7 75-inch man

9 Kershaw because his ERA was 2.3 standard deviations below the National League mean ERA, while Hernandez’s ERA was 1.91 standard deviations below the American League’s mean ERA.

11 100m back because for the 100m back he is 3.39 standard deviations below the mean and for the 200m back he is 3.05 standard deviations below the mean.

13 239

15

  1. 15% of 3-5 month old males have head circumferences that are 41cm or less while 85% of 3-5 month old males have head circumferences that aremore than 41cm.

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

  3. That males are getting taller because the heights at each percentile decrease as the age increases.

22

  1. (hint the mean = 10.08, standard deviation = 1.885), -1.2

  2. Q1 is 9.15, Q2 is 9.95, Q3 is 11.1

  3. 1.95

  4. The lower fence is 6.22, the upper fence is 14.03. Yes, 5.7.

25 574 minutes

3.5

3

  1. Right skewed

  2. 0, 1, 3, 6, 16

4

  1. Symmetric

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

5

  1. 40

  2. 52

  3. y because it has a larger range.

  4. Symmetric because the median is in the center and the whiskers are around the same length.

  5. Skewed right because the median is to the left and the right whisker is longer than the left.

6

  1. 16

  2. 22

  3. y because it has a larger range.

  4. Yes, 30

  5. It is skewed left because the distance from the median to Q1 is more than the distance from the median to Q3. Also the left whisker is longer than the right whisker.

7

dat1 <- c(60,68,77,89,98)

boxplot(dat1)

8

dat2 <- c(110,140,157,173,205)

boxplot(dat2)

9

dat3 <- c(42,43,46,46,47,
         47,48,49,49,50,
         50,51,51,51,51,
         52,52,54,54,54,
         54,54,55,55,55,
         55,56,56,56,57,
         57,57,57,58,60,
         61,61,61,62,64,
         64,65,68,69)

  1. 42, 50.5, 54.5, 57.5, 69 (note data is in order)

boxplot(dat3)

  1. Symmetric with an outlier.

10

dat3 <- 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,
          10.0, 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)

  1. 7.2, 9, 10, 11.2, 16.4 (note data is in order)

boxplot(dat3)

  1. Right skewed with an outlier.