3.4

  1. The z-score for the 34 week gestation period baby is -.3, and the z-score for the 40 week gestation period baby is -.43; the 40 week baby weighs less relative to the gestation period since the z-score is lower.

  2. A 75 inch man is relatively taller than a 70 inch woman.

  3. Hernandez had the better year, because his ERA was 2.14 standard deviations below the average, while Johnson’s ERA was 1.48 standard deviations below average.

  4. Power had the more convincing win, because he was 1.76 standard deviations below the average, while Franchitti was 1.48 standard deviations below the average.

  5. The minimum score than an applicant must make in order to be accpeted is 239.

    1. 15% of males aged 3-5 months have heads that measure 41 cm or less in circumference; 85% of males aged 3-5 months have heads that measure greater than 41 cm in circumference.
    1. The z-score of the hemoglobin of Blackie is -1; this means that Blackie the cat is 1 standard deviation away from the average; Blackie has less than the average.

  1. Q1 = 8.9 Q2 = 9.95 Q3 = 11.2

  2. IQR = 2.3 –> this meausres how far the median is from the max or the min

  3. The Lower Fence is 5.45, and the Upper Fence is 14.65 –> there are no outliers

  1. The cuttoff point is 1167.675

3.5

  1. 0,1,3,6,16 –> skewed right

  2. -1,2,5,8,11 –> bell

    1. 40

  1. 51

  2. variable y has more dispersion because its minn, max, and in between values of measurement are more spread out

  3. variable x is bell shaped, because there is a relatively even amount before and after the mean

  4. variable y is skewed right, since there are more variables to the left of the mean

    1. l6

  1. 22

  2. x has more dispersion because there is an outlier

  3. y is left skewed because most of the data is clustered toward the right

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

boxplot(this_data, horizontal = T)

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

boxplot(my_data, horizontal = T)

    1. 42, 50.5, 54.5, 57.5, 69
that_data <- c(42, 50.5, 54.5, 57.5, 69)
boxplot(that_data, horizontal = T)

  1. this is bell curved because the data is symmetrical
    1. 7.2, 8.9, 9.95, 11.2, 16.4
cool_data <- c(7.2, 8.9, 9.95, 11.2, 16.4)
boxplot(cool_data)

  1. this data is bell curved because the data is symmetrical