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“Whenever I see this”

BOOTSTRAPPING Sometimes sample means/medians are closer to the population means than others. One solution to reduce the level of uncertainty of our estimate is to take many samples. “Whenever I see this”. “ I remember this”.

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“Whenever I see this”

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  1. BOOTSTRAPPINGSometimes sample means/medians are closer to the population means than others. One solution to reduce the level of uncertainty of our estimate is to take many samples.

  2. “Whenever I see this” “ I remember this” By using many samples we can be fairly confident that the true median is somewhere in the blue band. The process called bootstrapping can be used to approximate the level of uncertainty associated with point estimates from one sample.

  3. The point of Bootstrapping is: • Take many (100s, 1000s) resamples (with replacement) and observe the changes of statistical interest. This allows us to observe the level of variability present. • We can also limit the more extreme values that the statistic has taken and only look at the middle 95%.

  4. Now that you know how to import data into N-Zight… (Page 157 Q2)

  5. 2.a. Median = 268mg/dL Blood • Note that re-sampling means taking a sample with replacement. That is why you may end up with different numbers of the same values.

  6. 1000 resamples

  7. Now you can see more clearly where the true median may lie

  8. To answer part b…Confidence Interval for the population median: 234≤268 ≤280

  9. c. What population can we apply this inference?

  10. Coronary care patients in north-eastern USA two days after a heart attack. Not we cannot apply this to an international population.

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