You have imported data into MODELER and have found many records with invalid values. Which action on invalid values would change a null value to FALSE?

In the context of handling invalid values in data, particularly when you want to change a null value to FALSE, the correct action is to "Coerce." Coercion refers to the process of converting data from one type to another or modifying its state to fit a specific requirement. When you coerce a null value, you are indicating that any missing or undefined value should be replaced with a default or specified value, in this case, FALSE.

The concept of coercion is particularly useful in data pre-processing stages, where ensuring that all variables hold valid entries is crucial for maintaining integrity in predictive models. This process allows analysts to control how missing data is treated, thus affecting the outcome of analyses and predictions.

Other options, while they might suggest manipulation of data, do not directly achieve the desired effect of replacing a null value with FALSE. Understanding how coercion works within data manipulation tools can greatly enhance the quality of your predictive analytics work by ensuring that datasets are clean and usable.