READING 3.4 QUESTIONS # 5-15 ODDS

  1. Birth Weights: What is the z-score for a 34-week gestation period baby?

What is the z-score for the 40-week gestation period baby?

Which baby weighs less relative to the gestation period?

  1. Men versus Women: Who is relatively taller, a 74-inch man or a 70-inch woman?
  1. ERA Champions: Which player had the better year relative to his peers, Johnson or Hernandez? Why?
  1. IndyCar Races: Who had the more convincing victory?
  1. School Admissions: What is the minimum score that an applicant must make on the test to be accepted?
  1. Explain the meaning of the following percentiles
  1. 15% of males 3-5 months old are 41.0 cm or less.

  2. 90% of 2-year-old females have a waist circumfrence equal to or less than 52.7 cm.

  3. The 90th percentile represents 90% of men in that category, and in every age division, the 90th percentile decreased in value as age increased. Based on this information, it can be inferred that men are likely taller when they are in 20-29 years of age, and decrease in height slightly as they age.

READING 3.5 PROBLEMS #3-10

  1. Identify the shape of the distribution
  1. Determine the five-number summary
  1. Identify the shape of the distribution
  1. Determine the five number summary
  1. Use the side-by-side boxplots shown to answer the quetions that follow.
  1. To the nearest integer, what is the median of variable x?
  1. To the nearest integer, what is the third quartile of variable y?
  1. Which variable has more dispersion? Why?
  1. Describe the shape of the variable x. Support your position.
  1. Describe the shape of the variable y. Support your position.
  1. Use the side-by-side boxplots to answer the questions that follow.
  1. To the nearest integer, what is the median of variable x?
  1. To the nearest integer, what is the first quartile of variable y?
  1. Which variable has more dispersion? Why?
  1. Does the variable x have any outliers? If so, what is the value of the outlier(s)?
  1. Describe the shape of the variable y. Support your position.
  1. Exam Scores: Draw a boxplot of the exam scores.
your_data <- c(60, 63, 68, 68, 68,
               75, 75, 77, 79, 89, 
               89, 89, 93, 94, 98)
             
boxplot(your_data, horizontal = T, col = c("lightpink"))

fivenum(your_data)
## [1] 60 68 77 89 98
  1. Speed Reading: Draw a boxplot of the reading speed.
this_data <- c(110, 125, 140, 140,140,
               150, 152, 157, 160, 173, 
               173, 173, 180, 180,205)
             
boxplot(this_data, horizontal = T, col = c("palevioletred4"))

fivenum(this_data)
## [1] 110 140 157 173 205
  1. Age at Inauguration
  1. Find the five-number summary
  1. Construct a boxplot
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, col = c("salmon"))

  1. Comment on the shape of the distribution.
  1. Carpoolers
  1. Find the five-number summary
  1. Construct a boxplot.
our_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(our_data)
## [1]  7.20  9.05 10.00 11.20 16.40
boxplot(our_data, horizontal = T, col = c("plum1"))

  1. Comment on the shape of the distribution.