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Slide 1

• What does a Probability Model include?

Slide 2

• Includes:
• Sample Space & Corresponding probability

Slide 3

• What is the sample space?

Slide 4

• We call the set of all possible outcomes of an experiment

Slide 5

• The difference between an Event & an Outcome

Slide 6

• Whenever we do an experiment like flipping a coin or rolling a die, we get an outcome.
• ~ it is the response of an experiment
• An event is a set of outcomes. The event of rolling an even number with a die is the set
• ~ A list of outcomes in the experiment used for data.

Slide 7

• What is probability distribution?

Slide 8

• When we use a random variable to describe a chance process & a corresponding probability for each outcome.

Slide 9

• what is unique to a histogram?

Slide 10

• it has 2 quantitative variable

Slide 11

• What requirements must a probability satisfy?

Slide 12

• 1) Every probability is a number between 0 and 1.
• 2) The sum of all the probabilities is equal to 1

Slide 13

• What does S.O.C.S stand for?

Slide 14

• Shape
• Outlier
• Center
• Spread

Slide 15

• The difference between an outlier and a extreme value is...?

Slide 16

• Outlier
• IQR = Q3 -Q1
• first quartile – 1.5 * IQR = Answ
• third quartile + 1.5 * IQR = Answ
• Extreme Values:
• Is something that is visually determined, not calculated.

Slide 17

• If you notice you have extreme values what should you use to measure spread?

Slide 18

• The IQR and Range are resistant to extreme values; therefore, these should be used to measure spread.

Slide 19