4 ms·

Half a standard deviation is 8 IQ, and effect size has nothing to do with significance.

sigmoid10 3y ago
What are you talking about? Statistical significance is directly calculated from effect size and standard deviation. https://en.wikipedia.org/wiki/Statistical_significance https://en.wikipedia.org/wiki/Statistical_significance
- drawkward 3y ago
  The standard deviation referred to in the article is the effect size, and not the standard error of that estimate, which is what would be used to determine its significance.
  - sigmoid10 3y ago
    No, that's just wrong. See the original source: https://journals.sagepub.com/doi/abs/10.1111/1467-9280.t01-1-01430 https://journals.sagepub.com/doi/abs/10.1111/1467-9280.t01-1...
    - drawkward 3y ago
      Nice link to a paywalled source.
    - icegreentea2 3y ago
      Thanks to scihub, we get the paragraph: > Point estimates for effect size on all cognitive tasks were 0.164 > (SE = 0.028, n = 96, p = .05) for control groups and 0.478 (SE = > 0.029, n = 101, p = .01) for exercisers, suggesting that both groups > improved between Times 1 and 2. However, the control groups’ im- > provement was about 1/8 a standard deviation, whereas the exercise > groups’ improvement was nearly 1/2 a standard deviation, on average. > Both values are significantly different from zero, and from each other > (see Table 1). Earlier in the paper they define their effect size as: g = (M_Post - M_Pre )/SD_P , where M_Pre is the preintervention mean task performance, M_Post is the postintervention mean, and SD_P is the pooled standard deviation. I think the standard deviation mentioned is relative to overall population spread of cognitive performance, given that standard errors of the effect size are given separately?
- rfrey 3y ago
  > What are you talking about? Statistical significance is directly calculated from effect size and standard deviation. But it's not about how big the effect is. It's how likely that the effect was or was not due to chance. A very small effect can be statistically significant. You missed "sample size" in your list above - a big sample size can help you show a small effect is probably not chance.

What are you talking about? Statistical significance is directly calculated from effect size and standard deviation. https://en.wikipedia.org/wiki/Statistical_significance https://en.wikipedia.org/wiki/Statistical_significance

drawkward 3y ago
The standard deviation referred to in the article is the effect size, and not the standard error of that estimate, which is what would be used to determine its significance.
- sigmoid10 3y ago
  No, that's just wrong. See the original source: https://journals.sagepub.com/doi/abs/10.1111/1467-9280.t01-1-01430 https://journals.sagepub.com/doi/abs/10.1111/1467-9280.t01-1...
  - drawkward 3y ago
    Nice link to a paywalled source.
  - icegreentea2 3y ago
    Thanks to scihub, we get the paragraph: > Point estimates for effect size on all cognitive tasks were 0.164 > (SE = 0.028, n = 96, p = .05) for control groups and 0.478 (SE = > 0.029, n = 101, p = .01) for exercisers, suggesting that both groups > improved between Times 1 and 2. However, the control groups’ im- > provement was about 1/8 a standard deviation, whereas the exercise > groups’ improvement was nearly 1/2 a standard deviation, on average. > Both values are significantly different from zero, and from each other > (see Table 1). Earlier in the paper they define their effect size as: g = (M_Post - M_Pre )/SD_P , where M_Pre is the preintervention mean task performance, M_Post is the postintervention mean, and SD_P is the pooled standard deviation. I think the standard deviation mentioned is relative to overall population spread of cognitive performance, given that standard errors of the effect size are given separately?
rfrey 3y ago
> What are you talking about? Statistical significance is directly calculated from effect size and standard deviation. But it's not about how big the effect is. It's how likely that the effect was or was not due to chance. A very small effect can be statistically significant. You missed "sample size" in your list above - a big sample size can help you show a small effect is probably not chance.