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Confidence Intervals—One Population Mean and Proportion Testing
Confidence Intervals—One Population Mean and Proportion Testing

95% confidence intervals
95% confidence intervals

Package `mapStats`
Package `mapStats`

... Description When using classIntervals to compute classes, occasionally there are rounding errors so that when the data is plotted and the class breaks are used for colors, for instance, the rounding error may cause a value to not be plotted with the right color, or to not be plotted at all. For this ...
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... For example, before an election a sample of voters is asked how they will vote. With this information a prediction is made on how the population of eligible voters will vote. In collecting samples, great care and expense is usually taken to make the selection as free from prejudice as possible, and ...
Descriptive Statistics
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Probability and Statistics - Tarleton State University
Probability and Statistics - Tarleton State University

... The median of the data is the middle number if there are an odd number of data points or the average of the two middle numbers if there is any even number of data points. This class has 31 students so the median is the data point that is in the 16th position in the ordered data set. The median is 6 ...
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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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