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13 Cards in this Set
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"My computer has a 85% chance of never crashing, 10% chance of crashing once, and a 5% chance of crashing twice." In this example what is: an outcome (mutually exclusive?), a probability, the sample space (Population), an event and is this a discrete or continuous random variable? |
Outcome: Computer crashing once (Mutually Exclusive) Probability: 85% chance of crashing once Sample Space: All possible outcomes (0, 1, 2) Event: 95% chance of crashing no more than once This is a discrete random variable (1, 2, 3 instead of 1.1, 1.2, 1.213, etc.) |
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In our last example: What would the probability distribution look like? The cumulative probability distribution? |
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For a continuous r.v. how would we create a probability distribution? A cumulative probability distribution? |
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What is the difference between conditional and unconditional probability? Give an example of each. |
Unconditional: An event happens and doesn't rely on another event needing to occur. Ex: What is the probability it will rain three days in a row? -->The answer to the question would be a joint probability. Conditional: The probability that an event will happen given/conditional on another event. Ex: What is the probability of getting heads next toss given you got tails on the last toss |
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"Given that a student is a econ major, what is the probability of being male?" How would you calculate the answer? |
1: Calculate the joint probability of a male econ student (P(male) * P(Econ)), then divide the result by P(Econ). |
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"My computer has a 85% chance of never crashing, 10% chance of crashing once, and a 5% chance of crashing twice." What is the expected value of computer crashes? What does it mean?
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The expected value of computer crashes is .2, this means over a period of time, after using your computer say 100 times. It will be expected on average to crash 20 times. |
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What is the difference between the variance and the standard deviation? Why do we use the standard deviation |
Variance is the dispersion around the mean (or expected value of the square of the deviation of y from its mean), while standard deviation is the square root of the variance. We use the standard deviation as the variance uses the units of the square of Y, making it awkward to interpret. |
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If the skewness comes out to be positive what does that mean? |
The graph has a long right tail. |
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Why do we use correlation instead of co-variance? |
Co-variance multiplies the units of x by units of y making interpretation difficult. Not so much the case for correlation. |
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What does it mean for the co-variance when X and Y are independent? What about the correlation? |
co-variance is zero, which means correlation is zero. |
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In our picture is the joint probability distribution of Y (how long the commute is) and X (whether or not it's going to rain). For each total shown, describe what each one means. INSERT PICTURE |
30%: Chance of rain 70%: Chance of no rain 22%: Chance of long commute 78%: Chance of short commute |
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In a given population of two-earner male-female couples, male earning have a mean of $40,000 per year and a standard deviation of $12,000. Female earnings have a mean of $45,000 per year and a standard deviation of $18,000. |
PLEASE FINISH AFTER ASKING TEACHER |
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Realistically we have to use samples from a population to estimate our: mean, S.D., Variance. Here is each one's equation: |
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