What is t test?
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What do you do as a data scientist?
A test has a true positive rate of 100% and a false-positive rate of 5%. There is a population with a 1/1000 rate of having the condition the test identifies. Considering a positive test, what is the probability of having that condition?
What is the aim of a/b testing?
Among python and r, which one is generally preferred for text analytics?
Treating a categorical variable as a continuous variable would result in a better predictive model?
How and by what methods data visualizations can be effectively used?
Which objects are iterated in python?
How do you use sql in sas, python, r languages?
When underfitting occurs in a static model?
What is collaborative filtering?
Can you cite some examples where a false negative important than a false positive?
For linear regression, what are some of the assumptions a data scientist is most likely to make?
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