Nov 4, 2016 · Can somebody explain how the properties of logs make it so you can do log linear regressions where the coefficients are interpreted as percentage changes?

I am currently working to build a model using a multiple linear regression. After fiddling around with my model, I am unsure how to best determine which variables to keep and which to …

Aug 23, 2021 · I am trying to match a ~60k observation data set, where the treatment (annual days of sun exposure) is continuous. The data also has several confounders, some of which …

But an important note is that the test is valid, even if the data is not approximately normal, if the sample size is large enough. The justification is a bit round about (Slutsky's theorem + t …

Sep 12, 2018 · I understand that with log-transformed data, the coefficient of variation (CV) on the original scale is equal to sqrt (exp (sigma^2)-1), where sigma is the standard deviation of log …

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Sep 7, 2016 · The first method is no resampling test of which I'm aware in the literature. It seems like your goal, by resampling X X and Y Y independently, is to generate data under the null …

The 5 datapoints are 5 comparable home sales (similar in size, lot, location, # of bedrooms, etc...). If you run such a model, the software will say you need one more datapoint than variables.

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I have two questions about confidence intervals: Apparently a narrow confidence interval implies that there is a smaller chance of obtaining an observation within that interval, therefore, our acc...