10-2 Regression 539 Regression Access tech supplements, videos, and data sets at www.TriolaStats.com TECH CENTER Statdisk 1. Click Analysis in the top menu. 2. Select Correlation and Regression from the dropdown menu. 3. Enter the desired significance level and select the columns to be evaluated. 4. Click Evaluate. 5. Click Scatterplot to obtain a scatterplot with the regression line. StatCrunch 1. Click Stat in the top menu. 2. Select Regression from the dropdown menu, then select Simple Linear from the submenu. 3. Select the columns to be used for the x variable and y variable. 4. Click Compute! 5. Click the arrow at the bottom of the results window to view the scatterplot with regression line. Minitab 1. Click Stat in the top menu. 2. Select Regression from the dropdown menu and select Regression—Fit Regression Model from the submenu. 3. Under Responses select the column that contains the dependent y values. Under Continuous predictors select the column that contains the independent x values. 4. Click OK. The regression equation is included in the results. Scatterplot 1. Click Stat in the top menu. 2. Select Regression—Fitted Line Plot from the dropdown menu. 3. Select the desired columns for the y variable and x variable. 4. Select Linear under Type of Regression Model and click OK. TIP: Another procedure is to click on Assistant in the top menu, then select Regression, and Simple Regression. Complete the dialog box to get results, including the regression equation. TI-83, 83 84 Plus Calculator 8 us Ca cu ato 1. Press K, then select TESTS in the top menu. 2. Select LinRegTTest in the menu and press [. 3. Enter the list names for the x and y variables. Enter 1 for Freq and for b & r select 3 0 to test the null hypothesis of no correlation. 4. Select Calculate and press [ to view results, which include the y-intercept (a) and slope (b) of the regression equation. R R commands: Regression results (y intercept and slope): lm1y=x2 Additional regression details: summary1lm1y=x2 2 A complete list of R statistical commands is available at TriolaStats.com Excel XLSTAT Add-In 1. Click on the XLSTAT tab in the Ribbon and then click Modeling data. 2. Select Linear regression from the dropdown menu. 3. Enter the range of cells containing the Y>Dependent variable data and X>Explanatory variable data. Check the Quantitative box under X>Explanatory variable. If the first data row includes a label, check the Variable labels box. 4. Click the Outputs tab and ensure Correlations and Analysis of variance and Prediction and residuals are checked. 5. Click OK, and the equation of the regression line will be displayed in the results. Excel (Data Analysis Add-In) 1. Click on the Data tab in the Ribbon and then click the Data Analysis tab. 2. Select Regression under Analysis Tools and click OK. 3. For Input Y Range enter the data range for the dependent y variable. For Input X Range enter the data range for the independent x variable. 4. Check the Labels box if the first row contains a label. 5. Check the Line Fit Plots box and Residuals Plots box and click OK to display the results. In the Coefficients table, the slope is labeled X Variable (or data label) and the y-intercept is labeled Intercept. TIP: The displayed graph will include a scatterplot of the original sample points along with the points that would be predicted by the regression equation. You can obtain the regression line by connecting the “predicted y” points.
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