![]() ![]() Next, enter some guess values for m and b into some cells on the worksheet. ![]() ![]() Let’s start again with the x- and y- data we had before. Use the Solver to find values of the slope and intercept that minimize the total error.Calculate the error between the calculated y-values and the y-data.Calculate new y-values based on those guess values.Enter “guess-values” for the slope and intercept of the equation.It will also introduce you to the possibilities for more complicated curve fitting using Excel. I’ve included it here because it provides some understanding into the way that the previous linear regression methods work. Fortunately, it will probably be unnecessary to ever use this method for simple linear regression. This method is more complex than both of the previous methods. That means we can use them dynamically in a calculation somewhere else in the spreadsheet. This was obviously more work than using a trendline, but the real advantage here is that the slope and y-intercept values have been output to a cell. ![]()
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