## Classical predicting

In the previous chapters, we became familiar with data samples and time series and got to know how to define their parameters, which means we were able to predict future values. As a matter of fact, this is classical prediction. However, if the statistical tools seems a bit difficult for you and there is no time to gain an understanding, you can use a quicker solution—the `Predict`

function. After receiving an input data array, it immediately issues a predicted value by keeping all the calculations behind the scenes:

In this case, we took a preliminary dataset—note the list entry in the format: input data -> value. Then, using the `Predict`

function, we obtained `PredictorFunction`

that can output any prediction value depending on the input data. For example, if the input value is equal to 4, the output will be 5.47. After reviewing our data, Mathematica came to the conclusion that the best model for prediction is linear regression. With the graph that we have built by successively...