Chapter 6: Probability Distributions

discrete random variable

a quantitative random variable that can only assume a finite number of values or a countable number of values

continuous random variable

a quantitative random variable that can assume any of the countless number of values in one or more intervals

mean of a probability distribution

represents the expected value, which is the long-term average outcome of a random variable if an experiment is repeated many time

uniform distribution

a probability distribution where every outcome in a given range has an equal chance of occurring

normal distribution

symmetric, single-peaked, bell-shaped, the mean is in the center, mean=median

Emperical Rule (68-95-99.7 Rule)

Approximately 68% of the observations fall within one SD of the mean
Approximately 95% of the observations fall within 2 SD of the mean
Approximately 99.7% of the observations fall within 3 SD of the mean

What does N(μ,σ) mean?

a normal distribution curve with a mean μ and standard deviation