Calculation of Confidence Intervals for Least Squares

Confidence Intervals for Slope and Intercept Parameters

In the last section, we calculated the best fit line for a sample of data. However, these data are subject to random sampling error, meaning that someone else could come later, perform the same experiment (x-values), and get different experimental results (y-values).

Therefore, our data are random variables, and the slope and y-intercept we calculate using those data are also random variables, chosen from distributions around the true (population) slope and y-intercept.

The true relationship between x and y is written y = b x + a. How close are the random variables a and b to the population parameters b and a?

Earn ASCLS P.A.C.E.® credits for your state clinical laboratory personnel license. Visit LabCE.com for medical laboratory technician continuing education.

Linear Regression Analysis course details »

Learn more about medical technologist continuing education for MTs, MLTs, and other lab personnel »

Get information on laboratory compliance training for clinical and medical laboratories »