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Study Guide for the Midterm
Study Guide for the Midterm

... population? What shape would the polygon take? 13. Study how the properties of sampling distributions can give us a way to gain insight into population parameters by merely using sample data. 14. Be sure that you can say what the standard error is in English. Be able to calculate the standard error: ...
Standardization, percentiles, and the normal curve
Standardization, percentiles, and the normal curve

... demonstrations. . . but if you ever have occasion to use “computer-intensive” statistics such as bootstrapping, jacknifing, or Monte Carlo simulation, then you will need to become familiar with random number generation in R. For now, let’s just generate random numbers for the purposes of illustratin ...
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Confidence Interval
Confidence Interval

... be too costly, so you did some sampling. If you were to survey every college graduate, then you would be 100% confident of your estimation. However, you did not, so your estimation must have some statistical legitimacy. This legitimacy comes from how confident you are of you estimation. So you can b ...
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Days to recover from cold Treated with multivitamin

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Lab #18 - BetsyMcCall.net

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... metric ruler is lined to 1mm,so the limit of uncertainty of the ruler is +/- 0.5 mm.) If the room temperature is read as 25 degrees C, with a thermometer that is scored at 1 degree intervals – what is the range of possible temperatures for the room? (ans.s +/- 0.5 degrees Celsius - if you read 15oC, ...
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PDF

Statistical Hypotheses
Statistical Hypotheses

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Inference for a Population Mean Statistics 111

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Handout - DigitalCommons@CalPoly

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... The points (data) doesn’t change, so they are just as far away as they were with a smaller sample. The statistics are now closer to the population parameters: 1, 0 and . D. All of the above are false. E. All of the above are true. 9. Which of the following is/are true? You need the formula: b1 = ...
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Basic statistics: a survival guide

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Misuse of statistics

Statistics are supposed to make something easier to understand but when used in a misleading fashion can trick the casual observer into believing something other than what the data shows. That is, a misuse of statistics occurs when a statistical argument asserts a falsehood. In some cases, the misuse may be accidental. In others, it is purposeful and for the gain of the perpetrator. When the statistical reason involved is false or misapplied, this constitutes a statistical fallacy.The false statistics trap can be quite damaging to the quest for knowledge. For example, in medical science, correcting a falsehood may take decades and cost lives.Misuses can be easy to fall into. Professional scientists, even mathematicians and professional statisticians, can be fooled by even some simple methods, even if they are careful to check everything. Scientists have been known to fool themselves with statistics due to lack of knowledge of probability theory and lack of standardization of their tests.
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