Alternatively, we can use ExcelвЂ™s Regression data analysis tool or, as we have done on the left side of Figure 2, by using the Real Statistics Linear Regression data analysis tool.ДЇigure 2 вЂ“ Calculation of Confidence and Prediction Intervals We next perform a regression analysis using columns C, D and E as the independent variables and column B as the dependent variable. Observation: Click here for proofs of the above formulas.Д®xample 1: Find the 95% confidence and prediction intervals for Poverty where Infant Mortality is 7.0, White = 80 and Crime = 400 based on the data in Example 2 of Multiple Regression Analysis using Excel, which is reproduced in Figure 1 (in two blocks to fit better on the page). Here, the square-root term is called the standard error of the prediction. The 1 вЂ“ О±В predictionВ interval of Е· 0В is therefore The prediction interval is calculated in a similar way, except that now the variance is the variance of the residual y в€’В Е·, which is Here t crit is the critical value of the t distribution with df Res = nВ в€’ kВ в€’ 1 degrees of freedom with significance level О±/2, i.e. The 1 вЂ“ О± confidence interval for the true value of Е· 0В is therefore If X 0 is the column array with values 1, x 01, x 02, вЂ¦, x 0 k, then an unbiased estimate of the standard error of Е· 0, called the standard error of the fit, is given by the formula

Where the regression coefficients b j are based on the n Г— ( k +1) data array X (with ones in the first column).ДЇor any specific values of the x j, say x 01, x 02, вЂ¦, x 0 k, we have the predicted value

LetвЂ™s assume that we have a regression line

How to add phstat in excel