QMS 202 Lecture Notes - Saccharomyces Cerevisiae, Linear Regression, Yeast

• School: Ryerson University
• Department: Quantitative Methods
• Course: QMS 202
• Professor: Charles Barkley

Document Summary

In this techskills module, we take a given data set and fit an appropriate function to the data. The formal process of fitting a function to a given data set is called regression. We start with fitting the simplest type of function, a linear function. Linear regression is the process of fitting a straight line to a data set. A linear function has the form y = ax + b. Hence, the task of linear regression is to determine values for a and b that create the straight line that best fits the given data. For example, we consider a data set from sullivan and sullivan, precalculus enhanced with graphing utilities, second. Our first task is to enter the data set into the casio. Fortunately, the casio makes this a simple task. Turn the calculator to select the stat menu. A spreadsheet is on, and then press the now displayed.