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Presentation
Presentation

... service is computed. Which one of the following would produce a confidence interval with larger margin of error? A. Using a sample of 1000 postal employees. B. Using a confidence level of 90% C. Using a confidence level of 99%. D. Using a different sample of 100 employees, ignoring the results of th ...
Section 8-R
Section 8-R

... service is computed. Which one of the following would produce a confidence interval with larger margin of error? A. Using a sample of 1000 postal employees. B. Using a confidence level of 90% C. Using a confidence level of 99%. D. Using a different sample of 100 employees, ignoring the results of th ...
PPT
PPT

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... Results from one child's three diets are not independent. The three results are probably clustered around a set-point for that child. The analysis must incorporate this possible correlated clustering. If the software is just given the 3x140 outcomes without distinguishing the individual children, th ...
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... R is a statistical software system for data analysis and graphics, developed by Ihaka and Gentleman of University of Auckland Department of Statistics (1995), and it is considered a dialect of S and S-Plus. R is freely distributed and has many built-in functions for statistical analysis and excellen ...
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... Refer to Exhibit 9-1. If the test is done at a .05 level of significance, the null hypothesis should a. not be rejected b. be rejected c. Not enough information is given to answer this question. d. None of the other answers are correct. ...
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... – A container-filling machine is believed to fill 1 liter containers so consistently, that the variance of the filling will be less than 1 cc (.001 liter). – To test this belief a random sample of 25 1-liter fills was taken, and the results recorded (Xm12-03) – Do these data support the belief that ...
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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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