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However, they must be calculated separately when Solver or other regression functions are employed. Fixing the number of significant digits is done by following these steps. R2s are easily determined using Excels Trendlines. You will see that the r2 value is much higher. Excel randomly decides the number of digits displayed in the trend line equation. The regression equation is reported as y 63.79x 13.96 and the r2 0.4356. I have attached the Excel file with my data on and pasted below the stata regression no constant output. You then have Excel plot the trend line and report the equation and the r2 value. The link you post certainly helps a little toward understanding why. Usually I would avoid Excel entirely for such analysis other than having a very quick look at the data, but, this time I feel it may have flagged up an important issue. Would anyone be able to help with a reason for why these values are different, suggest which ones are the correct value or have another solution that will allow me to run the regression and gain correct r2 and significance values? Considering the data, it is the lower graph r2 values that look more appropriate. The r2 values that Stata and Excel give for the linear regression analysis are always much higher than those that appear when I "show r2 value" on the Excel graph. I have also run regression on the data in Stata and Excel using the noconst function to run the regression with a 0 intercept.
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I have plotted the data as scatterplots in Excel and added a trend line with a 0 intercept (a justifiable approach in the ecological research I am doing). I am running a linear regression on some data I have, with the model passing through the origin - ie.