- [Voiceover] Hypothesis testing is one of the most common…approaches to inferential statistics that you'll find.…The idea here is that you'll want…to directly test your theory.…There's a few steps that go into this.…First off is you want to calculate the probability…of X, whatever result you have,…what's the probability of that occurring by chance…if randomness is the only explanation?…And then, if that probability is low,…you reject randomness as a likely…explanation for your observed result.…
That's the basic principle of hypothesis testing.…You can think of this as being…especially useful in a few situations.…Hypothesis testing's very common…in scientific research where you're testing…a particular theory to see if the theory is valid.…It's also common in diagnostics…where you're trying to figure out how likely…a particular outcome is based on the results of a test.…And then, it's basically the general principle…behind go versus no go decisions,…when you're trying to see if you…pass a particular cut-off or criterion.…
Author
Released
7/27/2016- Assess the skills required for a career in data science.
- Evaluate different sources of data, including metrics and APIs.
- Explore data through graphs and statistics.
- Discover how data scientists use programming languages such as R, Python, and SQL.
- Assess the role of mathematics, such as algebra, in data science.
- Assess the role of applied statistics, such as confidence intervals, in data science.
- Assess the role of machine learning, such as artificial neural networks, in data science.
- Define the components of effective data visualization.
Skill Level Beginner
Duration
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Video: Hypothesis