How can I interpret a regression statistics table in Excel?

I assume you mean this:

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The "Coefficients" are the slope or y-intercept in this case. "HH SIZE" refers to the Slope, and of course, Intercept is the y-intercept.

If you multiply the Standard Error by #1.96#, you get the Associated Error for either the Intercept or the Slope. The Associated Error is basically the uncertainty you have.

For example, in a standard physics lab course, bare minimum, here's what you would need to know:

• Slope
• Intercept
• Slope Standard Error (#SE_"slope"#)
• Slope Associated Error (#AE_"slope"#)
• Intercept Standard Error (#SE_"int"#)
• Intercept Associated Error (#AE_"int"#)

The sample standard deviation is:

#s = sqrt(1/(N-1) sum_(i=1)^N (x_i - barx)^2)#

where #N# is the number of trials, #x_i# is each individual value, and #barx# is the average of said values.

The Standard Error is:

#SE = s/sqrt(N)#

where #s# is the standard deviation above, and:

#AE = 1.96*SE#

Here is an example of an Ohm's law analysis I did using a similar regression statistics table:

Oftentimes, even in a quantitative analysis course, you only need to further know the coefficient of determination #R^2#. The closer it is to #1#, the better it is, but it is only for a linear fit line.

Other than that, I have not had to use any other quantity on the regression statistics table in my 7 University semesters.