PSYCH 2300

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Author:
xx.chelsii
ID:
222231
Filename:
PSYCH 2300
Updated:
2013-06-03 18:19:18
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Description:
Variability
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  1. Variability
    Provides a quantitative measure of the difference between scores in a distribution and describes the degree to which the scores are spread out or clustered together
  2. Range
    • The distance covered by the scores in a distribution, from the smallest score to the largest.

    URL=Xmax and LRL=Xmin
  3. Deviation
    • The distance from the mean
  4. Population Variance
    • Equals the mean squared deviation. Variance is the averaged squared distance from the mean
  5. Standard Deviation
  6. Standard Deviance
  7. Sum of Squares
    • SS
    • Or the sum of the squared deviation scores
  8. Definitional Formula for SS


    • 1. Find each deviation score
    • 2. Square each deviation score
    • 3. Add the squared deviations
  9. Computational formula of SS
    • 1. Square each score and then add the squared values
    • 2. Find the sum of the scores
    • 3. Then square this total
    • 4. Divide by
  10. Population Standard Deviation
  11. Population Variance
  12. SS for sample
    • Definitional Formula
    • Computational Formula
  13. Sample Variance
  14. Sample Standard Deviation
  15. Degrees of Freedom
    • For a sample of n scores, the degrees of freedom, or df, for the sample variance are defined as .
    • The degrees of freedom determine the number of scores in the sample that are independent and free to vary.
  16. Biased statistic
    A sample statistic is biased if the average value of the statistic either underestimates or overestimates the corresponding population parameter
  17. Unbiased Statistic
    A sample statistic is unbiased if the average value of the statistic is equal to the population parameter,(the average value of the statistic is obtained from all the possible samples for a specific sample size, n)

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