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During this Microsoft Excel 2016 advanced training tutorial video, we will continue with forecasting using linear equations and use the LINEST function with a single independent and dependent variable as an example.

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Welcome back to our course on Excel 2016 Advanced.
In this section we’re going to continue looking at forecasting using linear regression. But in this case we’re going to use the LINEST function.

Now the LINEST function offers a number of advantages and the first of them I’m going to concentrate on are one, not only can it forecast values for us but it can also indicate how likely it is that those forecasts are going to be good forecasts. It does this be evaluating how close the model that it’s using is to the observed values that we’re providing it with.

The second main advantage is that the LINEST function can be used in multivariate regression.
In this section I’m going to demonstrate LINEST with a single independent variable and a single dependent variable. And then in Exercise 04 which is covered in the next section you’re going to do some multivariate regression, but don’t worry too much about that at the moment because hopefully you’ll find it more straightforward than it may sound.

Now on the very subject of it being perhaps a little easier than it sounds, although I’m going to explain quite a few aspects of this as we go along I’m also going to refer you to a page in the Excel 2016 Help that explains what’s going on in quite a lot of detail. Now if you’re not really particularly interested in statistics or perhaps your math, you math is not really up to scratch you really don’t need to worry too much about all these details.

All you really need to be able to do is to apply this method and the Help sets out pretty much how to apply the method. I think of it sometimes in terms of driving the car. You can see how fast you’re going without necessarily knowing exactly how a speedometer works.

Now referring back to the preceding section the first method that I showed you there involves finding the slope and intercept for the best fit straight line through some pairs of values. And pretty much that’s what LINEST does as well. It gives you a slope and an intercept. But it can give you multiple slopes based on the use of multiple variables.

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