Multiple R = 0.97 indicates that the relationship is strong. Read More: How to Interpret ANOVA Single Factor Results in Excelįirst, observe the Regression Statistics table. Significance F = 0.01 R Square = 0.38 indicates that 38% of Y values can be explained by X values.Multiple R = 0.62 indicates that the relationship between the variables is not so strong but not so weak either.05 indicates the linear relationship is statistically significant.Ĭoefficients Table: The coefficients from this table are used to form the linear equation to represent the relationship between the variables.įirst, observe the Regression Statistics table below. A value closer to 1 indicates that a difference in the dependent variable can be explained by the difference in the independent variable(s) for most of the values.ĪNOVA Table: The Significance F is of the most importance here. It tells you the percentages of the dependent variable that can be explained by the independent variable(s). R Square: This is called the coefficient of determination.1, -1, and 0 indicate a strong positive, a strong negative, and no relationship respectively. It tells you how strong the linear relationship is between the independent and dependent variables. Multiple R: It is called the correlation coefficient.Regression Statistics: The two important values from this table are. We will briefly explain a few components from each part as the rest of them do not have much importance. The regression analysis output is divided into three different parts as follows. ⦿ Part-2: How to Interpret ANOVA and Other Regression Analysis Results in Excel Finally, you will see the following result in the specified location.Then, enter the cell reference where you want to get the analysis results. Next, mark the radio button for Output Range. Now select the Y values including labels for Input Y Range and all of the X values for Input X Range.
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