Remove 2009 Remove Experimentation Remove Measurement Remove Testing
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Understanding Simpson’s Paradox to Avoid Faulty Conclusions

Sisense

A new drug promising to reduce the risk of heart attack was tested with two groups. Continuing the previous example, let’s assume that blood pressure is known to be a cause for heart attack and the goal of the test drug is to reduce blood pressure. It really depends on the circumstances. Combined 13/60 = 21.67% 11/60 = 18.3%.

Testing 104
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The Lean Analytics Cycle: Metrics > Hypothesis > Experiment > Act

Occam's Razor

Sometimes, we escape the clutches of this sub optimal existence and do pick good metrics or engage in simple A/B testing. First, you figure out what you want to improve; then you create an experiment; then you run the experiment; then you measure the results and decide what to do. Testing out a new feature. Form a hypothesis.

Metrics 156
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Themes and Conferences per Pacoid, Episode 9

Domino Data Lab

Visualizations are vital in data science work, with the caveat that the information that they convey may be 4-5 layers of abstraction away from the actual business process being measured. measure the subjects’ ability to trust the models’ results. Information can get quite distorted after being abstracted that many times.

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6 Case Studies on The Benefits of Business Intelligence And Analytics

datapine

For example, in regards to marketing, traditional advertising methods of spending large amounts of money on TV, radio, and print ads without measuring ROI aren’t working like they used to. Everything is being tested, and then the campaigns that succeed get more money put into them, while the others aren’t repeated. The results?