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### Probability

A value between zero and one, inclusive, describing the relative possibility an event will occur

### Experiment

A process that leads to the occurence of one and only one of several possible observations

### Mutually Exclusive

The occurence of one event means that none of the other events can occur at the same time

### Empirical or Relative Frequency

The probability of an event happening is the fraction of the time similar events happened in the past

Empirical Probability= # of Times Event Occurs/Total Number of Observations

### Law of Large Numbers

Over a large number of trials, the empirical probability of an event will approach its true probability

### Subjective Probability

The likelihood of a particular event happening that is assigned by an individual based on whatever information is available

### Joint Probability

A probability that measures the likelihood two or more events will happen concurrently

### Independence

The occurence of one event has no effect on the probability of the occurence of another event

### Conditional Probability

The probability of a particular event occurring, given that another event has occurred

### Contingency Table

A table used to classify sample observations according to two or more identifiable characteristics

### Multiplication Formula

If there are m ways of doing one thing and n ways of doing another thing, there are m x n ways of doing both

### Probability Distribution

A listing of all the outcomes of an experiment and the probability associated with each outcome

### Characteristics of a Probability Distribution

1) The probability of a particular outcome is between 0 and 1

2) Outcomes are mutually exclusive events

3) The list is exhaustive- Sum of probabilities is 1

### Random Variable

A quantity resulting from an experiment that, by chance, can assume different values

### Variance of a Probability Distribution

Sum of (X values minus the mean) squared times the values expected probability

### Normal Probability Distribution

Bell-Shaped, Symmetrical, Asymptotic (Closer and closer to the x axis but never touches it)

### Z Value

The signed distance between a selected value, designated X, and the mean, divided by the standard deviation(X-Mean/Standard Deviation)

### 4 Characteristics of a Probability Distribution

1) Outcome on each trial of an experiment either success of failure

2) Random variable counts the number of successes in a fixed number of trials

3) Probability of success and failure stay same for each trial

4) Trials are independent

### Hypergeometric Probability Distribution

When probability of success does not remain teh same from trial to trial

### 4 Characteristics Hypergeometric Probability Distribution

1) Outcome on each trial of an experiment either a success or failure

2) Random variable is number of successes in a fixed number of trials

3) Trials are not independent

4) Proability of a success changes for each trial

### Poisson Probability Distribution

Describes the number of times some event occurs during a specified interval

### 3 Characteristics of a Poisson Probability Experiment

1) Random Variable is number of times some event occurs during a defined interval

2) Probability of the event is proportional to size of the interval

3) Intervals do not overlap and are independent