Section 3.4 5-15 Odds, 22, 25

  1. Birth Weights
    34 week baby z score = (2400-2600)/660 = -0.30 40 week baby z score= (3300-3500)/470 = -0.43
    The 40 week old baby weighs less relatively

  2. Men Vs. Women
    The man is relatively taller because he had a higher z score

  3. ERA Champions
    Hernandez had a better year because his z score was more below the average ERA for the year than Johnson

  4. IndyCar Races
    Power had a more convincing win because he was farther below the race average than the other racer

13.x = (1.5*26)+200 = 239

  1. Percentiles
  1. 15% of the 3-5 month males have a circumference of 41 cm or less b. 10% of 2 year old females have a waist of 52.7 cm or greater
  2. The heights at each percentile groups is increasing with age, which shows that males are getting taller.
  1. Hemoglobin in Cats
  1. (7.8-10.08)/1.886 = -1.209 b.Q1 = 9.15, Q2 = 9.95, Q3 = 11.1
  2. IQR = 11.1-9.15 = 1.95 This tells us the spread between Q3 and Q1 is 1.95
  3. LF = 6.225, UF = 14.025
  1. Cutoff point is 574 minutes

Section 3.5 3-10
3.
a. Right Skewed
b. 0, 1, 3, 6, 16
4.
a. Symmetric
b. -1, 2, 5, 8, 11
5.
a. 40
b. 52
c. Y, it has a greater IQR which describes spread for box plots and quartiles
d. About symmetric, looks fairly in the middle of the line
e. Right Skewed, more on the left side of the middle
6.
a. 16
b. 22
c. Y, greater IQR
d. Yes, 29
e. Left Skewed, the box is more on the right side of the plot
7. Exam Scores

my_data <- c(60, 63, 68, 68, 68,
               75, 75, 77, 79, 89, 
               89, 89, 93, 94, 98)

boxplot(my_data, horizontal = T, main = "Exam Scores")

fivenum(my_data)
## [1] 60 68 77 89 98
  1. Speed Reading
my_data <- c(110, 125, 140, 140,140,
               150, 152, 157, 160, 173, 
               173, 173, 180, 180,205)
             
boxplot(my_data, horizontal = T, main = "Speed Reading")

fivenum(my_data)
## [1] 110 140 157 173 205
  1. Age at Inauguration
my_data <- 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)

fivenum(my_data)
## [1] 42.0 50.5 54.5 57.5 69.0
boxplot(my_data, horizontal = T, main = "Age at Inauguration")

  1. Carpoolers
my_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(my_data)
## [1]  7.20  9.05 10.00 11.20 16.40
boxplot(my_data, horizontal = T, main = "Carpoolers")