Please enable JavaScript.

Coggle requires JavaScript to display documents.

Ch 4 Intro to Variability - Coggle Diagram

- - - - Because the standard deviation measures distance from the mean, it is represented by a horizontal line or an arrow drawn from the mean outward for a distance equal to the standard deviation and labeled with σ or an s.
- - - - Variability describes the distribution of scores. Specifically, it tells whether the scores are clustered close together or spread out over a large distance. Usually, variability is defined in terms of distance.
      - Variability measures how well an individual score (or group of scores) represents the entire distribution. This aspect of variability is very important for inferential statistics, in which relatively small samples are used to answer questions about populations.
- - - - To find the sum of the squared deviations, the formula instructs you to perform the following sequence of calculations:
      - Find each deviation score: (X-µ)
      - Square each deviation score: (X-µ)2
      - Add the squared deviations.
      - The result is SS, the sum of the squared deviations.
  - - - Computational formula: SS = ΣX2 – (ΣX)2 ÷ N
      - The first part of this formula directs you to square each score and then add the squared values, ΣX2
      - The second part of the formula, you find the sum of the scores, ΣX , then square this total and divide the result by N.
      - Finally, subtract the second part from the first.
- - - - What would happen to the standard deviation if each score were multiplied by 2?