With all our talk about needing precision, accuracy, low variability and high validity, it can all start to get a bit daunting. We know that the more variable are our data sets, then the more data points we are going to need to get a result in which we can be confident. How can we tell if the data we are generating will provide us with an answer that means something?
Just how much is enough . . .?
Power Analysis | 7:36 mins
This session will have provided you with some initial ideas on how to evaluate data sets for statistical usefulness. You’ll see again that high precision, high accuracy and low variability are king when it comes to getting the most out of your data. Now, it isn’t always, or even often, possible to arrange all these to come together at the one time, so we need to understand
To review your knowledge of this module, please complete the following quiz. The quiz comprises assessment one.