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Copy file name to clipboardExpand all lines: chapter_07.md
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The CDF shows the cumulative probability: P(X ≤ 0) = 0.7 (just the negative test outcome) and P(X ≤ 1) = 1.0 (both outcomes).
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The CDF shows the step function: starts at 0 for x < 0, jumps to 0.7 at x=0 (the value when outcome is 0), stays flat at 0.7 until x=1, then jumps to 1.0 at x=1 (the value when including both outcomes 0 and 1).
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**Understanding PMF and CDF Charts**
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The CDF shows cumulative probabilities: P(X ≤ 0) = 0.9 and P(X ≤ 1) = 1.0.
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The CDF shows the step function: starts at 0 for x < 0, jumps to 0.9 at x=0, stays flat at 0.9 until x=1, then jumps to 1.0 at x=1.
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:::
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The CDF shows P(X ≤ k), the cumulative probability of getting k or fewer heads.
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The CDF shows the step function increasing from 0 to 1, representing the cumulative probability of getting k or fewer heads.
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:::{admonition} Example: Sales Calls with n = 20, p = 0.15
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:class: tip
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The CDF shows P(X ≤ k), the cumulative probability of getting k or fewer successful calls.
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The CDF shows the step function increasing from 0 to 1, representing the cumulative probability of getting k or fewer successful calls.
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:::
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The CDF shows P(X ≤ k), approaching 1 as k increases (eventually you'll succeed).
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The CDF shows the step function increasing from 0 toward 1 as k increases (eventually you'll succeed).
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:::{admonition} Example: Certification Exam with p = 0.6
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:class: tip
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The CDF shows P(X ≤ k), increasing toward 1 as the trial number increases.
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The CDF shows the step function increasing from 0 toward 1 as the trial number increases.
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