Statistical methods (correlation and regression) were still in their infancy, so Guerry relied on graphic comparisons of maps and semi-graphic tables.
In various fields of application, different terminologies are used in place of dependent and independent variables.
One common way to find the receptive field is to use linear regression to find which stimulus characteristics typically caused neurons to become excited or depressed.
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Most papers that employ Difference-in-Differences estimation use many years of data and focus on serially correlated outcomes but ignore that the resulting standard errors are inconsistent, leading to serious over-estimation of t-statistics and significance levels.
Around 1979, Anil Bera and Carlos Jarque while working on their dissertations on regression analysis, have applied the Lagrange multiplier principle to the Pearson family of distributions to test the normality of unobserved regression residuals and found that the JB test was asymptotically optimal (although the sample size needed to “reach” the asymptotic level was quite large).
Ordinary least squares, a method used in regression analysis for estimating linear models