JOUR 651 Lecture 85: Estimated Metrics

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A lot of times you might find metrics that don"t have a clear meaning or represent estimates instead of facts. There are some good uses for metrics that are estimated, but it"s better to have a solid ground of fact when working with metrics. Estimated metrics can turn into something that disguising how your metrics are really performing and can become dangerous if they are presented in this way. This is dangerous because you can start to think your performance is doing really well, when it"s not, and create an illusion to hinder improvement on your overall strategy. When you"re working with estimates, you need to have causality. In analytics, you"re are always looking for the cause of why a certain performance happened and what the effects of that performance could be. Causality can help you in your though process of fitting estimated metrics to reality.

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