Week 6: discrete probability mass function, continuous probability density function, notation, concept

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7 Terms

1
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What is the discrete probability mass function?

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2
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What is the continuous probability density function?

The expected value is found using integration, but it’s easier to do w x h to find the area!

<p>The expected value is found using integration, but it’s easier to do w x h to find the area!</p>
3
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What is the expected value (mean) and variance for a probability density function?

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4
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What is the normal probability density function?

Referred to as gaussian distribution or bell curve

<p>Referred to as gaussian distribution or bell curve</p><p></p>
5
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What does the the expected value and variance mean in a bell curve?

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6
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What is the 68/95/99.7 rule? (empirical rule)

For any normal model:

  • 68% of the probability is between ± 1 of it’s expected value

  • 95% of probability is between ± 2 of its expected value

  • 99.7% of probability is between ± 3 of its expected value

<p>For any normal model:</p><ul><li><p>68% of the probability is between <span>± 1 of it’s expected value</span></p></li><li><p><span>95% of probability is between ± 2 of its expected value</span></p></li><li><p><span>99.7% of probability is between ± 3 of its expected value</span></p></li></ul><p></p>
7
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What is the a z-score?

A z-score gives the number of standard deivations that a value x, is above or below the mean!

  • - z score → lower than mean (left)

  • + z score → higher than mean (right)

<p>A z-score gives the number of standard deivations that a value x, is above or below the mean!</p><ul><li><p>- z score → lower than mean (left)</p></li><li><p>+ z score → higher than mean (right)</p></li></ul><p></p>