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Methods of Study Design – Experiments

Data Science 101

Some pitfalls of this type of experimentation include: Suppose an experiment is performed to observe the relationship between the snack habit of a person while watching TV. Bias can cause a huge error in experimentation results so we need to avoid them. Statistics Essential for Dummies by D. REFERENCES. McCabe & B.

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Changing assignment weights with time-based confounders

The Unofficial Google Data Science Blog

For example, imagine a fantasy football site is considering displaying advanced player statistics. A ramp-up strategy may mitigate the risk of upsetting the site’s loyal users who perhaps have strong preferences for the current statistics that are shown. One reason to do ramp-up is to mitigate the risk of never before seen arms.

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10 Fundamental Web Analytics Truths: Embrace 'Em & Win Big

Occam's Razor

Part of it is fueled by a vocal minority genuinely upset that 10 years on we are still not a statistically powered bunch doing complicated analysis that is shifting paradigms. As of 2010 I still have a lot more years that I spend in the traditional data warehousing / business intelligence world than in web analytics. Likely not.

Analytics 118
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Unintentional data

The Unofficial Google Data Science Blog

1]" Statistics, as a discipline, was largely developed in a small data world. More people than ever are using statistical analysis packages and dashboards, explicitly or more often implicitly, to develop and test hypotheses. Data was expensive to gather, and therefore decisions to collect data were generally well-considered.