![]() ![]() ![]() The data seems to confirm his hypothesis that push notifications are not accomplishing the company’s goals. The other half of users will not receive any push notifications at all.Īfter the test runs for 30 days, the executive analyzes the results and notices that there was no statistically significant improvement on engagement from the users who received push notifications. The test is established to send half of the app’s users a push notification every hour on the hour. Currently, users receive three push notifications every day on average. The executive decides to run an experiment to prove that push notifications do not increase engagement. Let’s say, for example’s sake, a mobile marketing executive believed that push notifications were intrusive and detrimental to the company’s goals (blasphemy!). Learn more about what a control group is or jump to our infographic for a visual guide to use control groups in A/B testing. This may lead you to wonder, how are control groups used in fields other than the physical sciences? And, how does a control group help combat biases? One common source of error within experimentation is confirmation bias.Ĭonfirmation bias is the tendency for experimenters to give their expected outcome too much weight when measuring results, leading to inaccurate findings. Since there is a lot of room for error within the scientific method, having a control group present is vital for accurate analysis. In a pharmaceutical drug study, for example, the control group receives a placebo, which has no effect on the body. So, what is a control group, scientifically speaking?Ī control group is a statistically significant portion of participants in an experiment that are shielded from exposure to variables. Any experimenter worth their salt will metaphorically season their experiment with what we in the business call a control group. Scientists have a method to their madness, conveniently known as the scientific method. ![]()
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