# Insignificant regression coefficients

Why doesn’t the text remove the variables whose coefficients are insignificant from the regression equation, using the original equation instead to estimate the independent variable?

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I don’t understand your question entirelly, but will try to explain something:

asubset wrote:

Why doesn’t the text remove the variables whose coefficients are insignificant from the regression equation, …

Some researchers state that it is not always a good idea to retire independent variables that depict insignificant coefficients from a statistical point of view, but that still shows sound economical explanation for the dependent variable. This is like “accepting” a less tight threshold for that specific “insignificant” variable. It is still upon the decision of the researcher to retire or keep the variable, tho.

asubset wrote:

using the original equation instead to estimate the independent variable?

Don’t understand this part of your question. Perhaps can you elaborate further your doubt?

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asubset wrote:

Why doesn’t the text remove the variables whose coefficients are insignificant from the regression equation, using the original equation instead to estimate the independent variable?

Data are noisy and a “large” p-value in one data set doesn’t actually say anything about whether that variable is truly part of the real regression function. As Harrogath mentioned, subject matter expertise should nearly always win over an arbitrary p-value. P-values themselves are random variables with incredible variability. People unfamiliar with statistics have a false sense of confidence in trivial things like p-values because there is mathematics used to estimate that quantity (and others). Mathematics is often precise, provable. Statistics and probability are entirely built on using mathematics and logic to estimate how imprecise and uncertain things are, but people often conflate statistics (uncertain) for mathematics (much more certain).