Editing 2048: Curve-Fitting
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===Cauchy-Lorentz (title text)=== | ===Cauchy-Lorentz (title text)=== | ||
{{w|Cauchy_distribution|Cauchy-Lorentz}} is a continuous probability distribution which does not have an expected value or a defined variance. This means that the law of large numbers does not hold and that estimating e.g. the sample mean will diverge (be all over the place) the more data points you have. Hence very troublesome (mathematically alarming). | {{w|Cauchy_distribution|Cauchy-Lorentz}} is a continuous probability distribution which does not have an expected value or a defined variance. This means that the law of large numbers does not hold and that estimating e.g. the sample mean will diverge (be all over the place) the more data points you have. Hence very troublesome (mathematically alarming). | ||
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Since so many different models can fit this data set at first glance, Randall may be making a point about how if a data set is sufficiently messy, you can read any trend you want into it, and the trend that is chosen may say more about the researcher than about the data. This is a similar sentiment to [[1725: Linear Regression]], which also pokes fun at dubious trend lines on scatterplots. | Since so many different models can fit this data set at first glance, Randall may be making a point about how if a data set is sufficiently messy, you can read any trend you want into it, and the trend that is chosen may say more about the researcher than about the data. This is a similar sentiment to [[1725: Linear Regression]], which also pokes fun at dubious trend lines on scatterplots. |