Chapter 2

Question 1

standardizing

Answer 1

converting an observation value to the number of standard deviations the value is from the mean

Question 2

z-score

Answer 2

a standardized observation value; z = (x-mean)/standard deviation

Question 3

Chebyshev’s inequality

Answer 3

the fundamental theorem that the probability that a random variable differs from its mean by more than k standard deviations is less than or equal to 1/ k ²

Question 4

mathematical model

Answer 4

an idealized description of a distribution

Question 5

density curve

Answer 5

a curve that is always on or above the horizontal axis and has an area of exactly 1 underneath it. Areas under the curve represent proportions of the population

Question 6

normal distributions

Answer 6

symmetric, unimodal and bell-shaped distributions

Question 7

empirical rule

Answer 7

68-95-99.7 = a theorem used to estimate the proportion of observations that fall between 1, 2 or 3 standard deviations on either side of the mean.

Question 8

Standard Normal Distribution

Answer 8

the normal distribution N(0,1) which has a mean of 0 and a standard deviation of 1. Every standardized variable has the standard normal distribution

Question 9

Normal Probability Plot

Answer 9

a scatter plot of the each value in a data (from least to greatest) set against its z-score or standardized value.