Timeline for Why does increasing the sample size of coin flips not improve the normal curve approximation?
Current License: CC BY-SA 4.0
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| Jan 29, 2019 at 22:03 | comment | added | Jeremy | @ChrisSnow ANOVA is a perspective in linear regression that focuses on whether or not different groups are, in fact, different by looking at variance (hence the name). The connection is that with too few repetitions, you can't actually tell the difference between groups, even though you have a lot of flips. The approximation to the normal curve gets bad, and the variance of each group is not different enough to conclude that anything is, in fact, different. | |
| Jan 29, 2019 at 20:36 | comment | added | Chris Snow | Thank you for the answer. Would you be able to elaborate on how ANOVA could be used in this context? | |
| Jan 29, 2019 at 14:10 | review | First posts | |||
| Jan 29, 2019 at 19:17 | |||||
| Jan 29, 2019 at 14:06 | history | answered | Jeremy | CC BY-SA 4.0 |