![]() ![]() Okay, now we have come to the end of this tutorial on regression analysis using Microsoft excel. In other words, attendance percentage affects the marks of a student. That means there is a linear relationship between the two variables. ![]() Therefore we can say that there is enough evidence to reject the null hypothesis. That means for a 1% increase in attendance, 0.96 marks are increased.Īlso, the p-value is very small when compared to the significance level. Because it takes the number of independent variables into the calculation. In fact, a more accurate one is the adjusted r-squared value which is 0.84. R – squared value being closer to 1 tells us that most of the variability in y is explained by the regression model. The “R squared” value also testifies that (Here r-squared = 0.85). When we look at our Scatter Plot, it is clear that there is a positive relationship between the two variables. MS Excel Regression Results Interpretation of Regression Analysis ![]() Also, this produces a Normal Probability Plot. Select this option if you need Normal Probability information in your results. If you are not interested in residuals, you can leave it blank. In this section, we can select information and plots on residuals. Or if you like to have the output in a new worksheet, select that radio button. You can give a cell reference if you need to display the output on the current worksheet. Here you can choose where you want your regression results to be displayed. This means that the response variable is zero when the predictor variable is zero. Also, If you need the regression line to cross 0 (zero), tick the checkbox named ‘Constant is Zero’. I will explain about the sections in this dialog box one by one Input Section Now you have a dialog box named “Regression” You can find it at the bottom part of the list. ![]() From the “Data Analysis” dialog box, select ‘Regression’. ![]()
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