| Tags | technical-assessment |
| Hard Prerequisites | |
| IMPORTANT: Please review these prerequisites, they include important information that will help you with this content. | |
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On Tilde you’ll notice that this card is asking for a link submission. Please don’t worry about submitting a link. You will be assessed according to TOPIC: Introduction to live assessments .
For each of the concepts covered below, the learner should know how to do the calculations by hand. If the learner only knows how to do this work using data science tooling (e.g. pandas) then they won’t be in a good position to apply the tools correctly or reason about their output.
The learner should be able to do simple calculations of probabilities. They should know when probabilities should be multiplied and when they should be added.
Here are a few sample questions: what is the probability of…
What is a hypothesis test and how do we set one up? Describe a simple hypothesis test, and the conditions under which we would accept an outcome as significant. Explain what are type I and type II errors. Know what the empirical rule is and be able to answer simple problems using it.
Suppose we want to test the hypothesis that more than 30% of households have internet access (with a significance level of 5%). We collect a sample of 150 households and find that 57 have access.
You should be able to set up the hypothesis test. Calculate the p-value under which we reject the null at the appropriate significance level.