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9 Cards in this Set
- Front
- Back
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Random Variable |
takes numerical values that describe the outcome of some chance process. |
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Probability distribution |
gives the possible values and their probabilities of a random variable. |
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discrete random variables |
assign a probability to every individual outcome, then add these probabilities to find the probability of the event. This idea works well if we can find a way to list all possible outcomes. |
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The probability distribution for a discrete random variable must have outcome probabilities that are between BLANK and that add up to BLANK. |
0 and 1, 1 |
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Mean (expected value, mu) of a discrete random variable |
multiply each possible value by its probability then add all the products. Used when all outcomes may not be equally likely. |
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For discrete random variables we use BLANK for spread. |
Standard Deviation |
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Variance of an Random Variable |
an average of the squared deviation (x1-mux)2 of the values of the variable x from its mean. |
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standard deviation |
the square root of the variance. It measures the variability of the distribution about the mean. |
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Continuous Random Variable |
x takes all values in an interval of numbers. The probability distribution of x is described by a density curve. The probability of any event is the area under the density curve and above the values of x that make up the event. |
