Mean, Median, Correlation, Standard Deviation, Five Number Summary and others. – Flashcards

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Mean
Mean
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The mean is the average of the numbers. (In other words it is the sum divided by the count)
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Median
Median
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The Median is the "middle" of a sorted list of numbers. (To find the Median, place the numbers in value order and find the middle.)
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Standard Deviation
Standard Deviation
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Standard deviation is a measure of the dispersion of a set of data from its mean. The more spread apart the data, the higher the deviation. Standard deviation is calculated as the square root of variance.
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Five Number Summary
Five Number Summary
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For a set of data, the minimum, first quartile, median, third quartile, and maximum. (A boxplot is a visual display of the five-number summary.)
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Correlation
Correlation
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A link between two variables is called a correlation. == Associations between variables, and if an association or a relationship exists between two variables, it means that the average value of one variable changes as the value of the other variable is changed.
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Simpson' Paradox
Simpson' Paradox
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Simpson's Paradox is a statistical phenomenon where the data seems to prove the reverse of the truth === (Simpson's Paradox is caused by a combination of a lurking variable and data from unequal sized groups being combined into a single data set. The unequal group sizes, in the presence of a lurking variable, can weight the results incorrectly. This can lead to seriously flawed conclusions. The obvious way to prevent it is to not combine data sets of different sizes from a diverse sources.)
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Causation [ or causality]
Causation [ or causality]
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Causation, or causality, is the capacity of one variable to influence another. == The capacity of one variable to influence another. The first variable may bring the second into existence or may cause the incidence of the second variable to fluctuate. === (Note: Causation is often confused with correlation, which indicates the extent to which two variables tend to increase or decrease in parallel. However, correlation by itself does not imply causation.)
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