These numbers are extremely common in elementary statistics. r² is the coefficient of determination, and represents the percentage of variation in data that is explained by the linear regression. Little r is the coefficient of correlation, which tells how closely the data is correlated to the line. It turns out that the line of best fit has the equation: where. When you make the SSE a minimum, you have determined the points that are on the line of best fit. Now re-run the linear regression and we get two more statistics: Using calculus, you can determine the values of and that make the SSE a minimum. Press ENTER to paste it and ENTER again to confirm. If your calculator does not already, you can set it to display some correlation coefficients by pressing 2nd 0 to get to the catalog screen, then, since alpha-lock is automatically on, press x⁻¹ to go down to the “D” section and use the arrow buttons to scroll down to DiagnosticOn. Using this equation, we can say that we would expect X=4 workers to produce around Y=44 widgets, even though we have no actual data collected for X=4. You can use this Linear Regression Calculator to find out the equation of the regression line along with the linear correlation coefficient. This display means that our regression equation is Y = 10.5X+.1. Learn how to use the TI-30XS MultiView calculator to perform correlation and regression analysis and find the linear regression equation for a set of data points. The calculator will display your regression equation. When done, press STAT, CALC, 4 to select LinReg(ax+b). In the STAT list editor, enter the (X) data in list L1 and the Y data in list L2, paired so that the corresponding ((x,y)) values are next to each other in the lists.
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Using the Linear Regression T Test: LinRegTTest. The lists should automatically scale as you add more data. USING THE TI-83, 83+, 84, 84+ CALCULATOR. Now enter the X data into L1 and Y data into L2 by using the arrow buttons to select a cell, then pressing ENTER, typing in the corresponding number, and pressing ENTER again to confirm. We’re going to be using L1 and L2 for this tutorial–if either has data in it, clear the list by selecting the name with the arrow buttons and pressing CLEAR, then ENTER.
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Lets use the Ford F-150 data to show how to find the equation of the least-squares regression line on the TI-Nspire Here are the data: Miles driven. Next, press STAT, and ENTER to select the list editor. Least-squares regression lines on the calculator.