Download 5.2: Probability Distributions

5.2: Probability Distributions
By the end of class you will be able to
construct a probability distribution from
a data set and explain why it is a valid
probability distribution.
Vocabulary Review
• Variable: a characteristic or attribute that can
assume different values
• Random Variable: a variable whose value is
determined by chance
• Discrete Variable: variables that have a finite
number of possibilities or an infinite number of
values that can be counted (count)
• Continuous Variable: variables that can assume
an infinite number of values (measure)
Discrete or Continuous?
• Sum on two dice
• Discrete
• Temperature at 5:00
• Continuous
• # of hairs on your
head
• Discrete
• Weight of an apple
• Continuous
Discrete Probability Distributions
• A distribution that consists of the values a
random variable can take on and the
corresponding probabilities of the values.
• The probabilities can be theoretical or
experimental (observed)
• Sum of probabilities in sample space must
equal 1
• The probability of each event in the
sample space must be between 0 and 1
Discrete Probability Distributions
• X-axis: possible outcomes
• Y-axis: probabilities
Example: Letters in a Hat
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In a hat are the letters of “Mississippi”
Random Variable: X = Letter Selected
Construct a probability distribution
Explain why it is a probability distribution
Graph the probability distribution
Your Turn: Car Trips
Summarizer 3-2-1
• 3 things you learned today
• 2 facts about probability distributions
• 1 question you still have