LINEAR REGRESSIONS
Introducing the Topic
In this chapter, you and your students will learn how to use the Sharp graphing calculator to find the linear regression (best-fitting line) for a set of data points. A regression line is a linear model of the relationship between the dependent variable Y and the independent variable X. The model is denoted as Y = a + bX, where a is the Y-intercept and b is the slope of the regression line.
A third value, r, is calculated for each regression. The r value is the correlation coefficient, which is a measure of how well the line fits the data points, and it will range from -1 to 1. If r = -1 or 1, then the line intersects all the data points, and the data points are said to be in perfect-linear correlation. A positive sign indicates a direct relationship (as X increases, the Y increases), whereas a negative sign indicates an indirect relationship (as X increases, the Y decreases). Values of r close to -1 or 1 are said to reflect a strong linear correlation, and values close to 0 are said to reflect the absence of linear correlation.
38Linear Regressions/STATISTICS USING THE SHARP EL-9600
