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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.
38 Linear Regressions/STATISTICS USING THE SHARP EL-9600
LINEAR REGRESSIONS
Chapter eight