Unit 4: Probability Flashcards
Geometric Probability
Looking for “the first” success in n trials.
Binomial Probability
Looking for “x” number of success in n trials.
Random Variable
Variable that quantifies a set of outcomes
Model for a Discrete Random Variable
Table in which outcomes are on the top row and corresponding probabilities are on the second row
Distribution for a Discrete Random Variable
Histogram that shows the outcomes on the x-axis and probabilities on the y-axis.
Expected Value
Mean of a Random Variable. Sum of the product of outcomes and probabilities.
Independent Events
P(A and B) = P(A)×P(B)
Tree Diagram
Use when two events are dependent.
10% Condition
Can be used to explain independence if a Bernoulli trial fails the “independence” criteria
Bernoulli Trial
- Two outcomes (success/failure)
- Known probability of success
- Trials are independent
z-score
standardized score in the Normal Model
P(A|B)
Normal Model
Continuous Random Variable Distribution
Also called the Normal Probability Density Function
Used to find probabilities with z-scores
65-95-99.7 Rule
65% of the population is between 1 standard deviation from the mean.
95% of the population is between 2 sd’s from the mean.
99.7% of the population is between 3 sd’s from the mean.
Percentile
The percent of the population LESS THAN a certain number.