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    An introductory statistics study guide including definitions of terms and types of variables and scales.

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    Terms defined and/or explained: randomness, independence, continuous, discrete, and ranked variables, attributes, derived and transformed variables, nominal, ordinal, interval, and ratio scales, scale conversions, mode, median, mean, range, standard deviation, sum of squares, variance, degrees of freedom, normal distribution, parametric vs. non parametric, p-value, type I and II errors.

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    https://brainmass.com/statistics/quantative-analysis-of-data/6790

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    <b>Randomness</b> - each possible sample that could be drawn from the population has an equal probability of being drawn.<br><br><b>Independence</b> - choosing one individual does not in any way change the probability that any other individual will be chosen.<br><br><br>VARIABLES<br><br><b>Continuous variable</b> - any value in a range (ex: length, mass, temperature).<br><br><b>Discrete variable</b> - always whole numbers (ex: litter size).<br><br><b>Ranked variable</b> - Variables can be ranked with respect to relative magnitude. The only relationships expressed are =, <, or > (ex: dominance hierarchy).<br><br><b>Attributes</b> - can't be expressed quantitatively nor ranked (ex: male, female).<br><br><b>Derived variables</b> - rates, percentages, ratios <br><br><b>Transformed variables</b> - performing a mathematical operation to the original value (ex: pH).<br><br><br>SCALES<br><br><b>Nominal ...

    Solution Summary

    The solution discusses terms defined and/or explained: randomness, independence, continuous, discrete, and ranked variables, attributes, derived and transformed variables, nominal, ordinal, interval, and ratio scales, scale conversions, mode, median, mean, range, standard deviation, sum of squares, variance, degrees of freedom, normal distribution, parametric vs. non parametric, p-value, type I and II errors.

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