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Definition
| The degree to which the data are spread out |
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| The difference between the largest data value and the smallest data value (R) |
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| Largest data value - smallest data value |
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Definition
| For the i-th observation is (xi - mew) |
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| Sample deviation about the mean |
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Definition
| For the i-th observation is (xi - xbar) |
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| The sum of all deviations about the mean must equal |
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Definition
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| Population variance (sigma^2) |
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Definition
| The sum of the squared deviations about the population mean divided by the number of observations in the population (N) |
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| 1. Population variance, sigma^2 = |
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Definition
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| 2. Population variance, sigma^2 = |
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Definition
| Summation(xi^2 - (summation(xi)^2)/N)/N |
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Definition
| Determining the sum of the squared deviations about the sample mean and dividing it by n-1 |
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| 1. Sample variance, s^2 = |
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Definition
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Term
| 2. Sample variance, s^2 = |
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Definition
| Summation(xi^2 - (summation(xi)^2)/n)/n-1 |
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Term
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Definition
| Whenever a statistic consistently over/underestimates a parameter |
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Definition
| The number of independent ways by which a dynamic system can move without violating any constraint imposed on it |
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| Population standard deviation, sigma = |
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Definition
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| Sample standard deviation, s = |
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| Standard deviation typically represents |
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Definition
| A typical deviation from the mean |
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| The (larger/smaller) the standard deviation, the more dispersion the distribution has |
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Definition
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Term
| 1. Empirical Rule - Normal Distribution |
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Definition
| 1 standard deviation from the mean should include 68% of the data; 68% lies between (mew-1sigma) and (mew+1sigma) |
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| 2. Empirical Rule - Normal Distribution |
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Definition
| 2 standard deviations from the mean should include 95% of the data; 95% lies between (mew-2sigma) and (mew+2sigma) |
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Term
| 3. Empirical Rule - Normal Distribution |
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Definition
| 3 standard deviations from the mean should include 99.7% of the data; 99.7% lies between (mew-3sigma) and (mew+3sigma) |
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Term
| Chebyshev's inequality determines |
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Definition
| The minimum percentage of observations within a distribution for a given standard deviation |
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Term
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Definition
(1-1/k^2)100%
where k = standard deviation |
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