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np.array([1.0, 2.0]) + np.array([[1.0], [2.0]]) has which shape?

(2, 2)

(2,)

It raises an error

In pandas, what does df.groupby("city")["amount"].sum() return?

One row per original row, with the city's total added

One total per city

A single total over all rows

A column has 30 % missing incomes, mostly among young respondents. What's the main risk of dropping those rows?

The remaining sample no longer represents young respondents

The mean can no longer be computed

None, because dropping rows never changes an estimate

What does a 95 % confidence interval procedure guarantee?

There's a 95 % chance that a new observation falls inside this interval

Across repeated samples, about 95 % of such intervals contain the true value

95 % of the data lies inside the interval

Why does random assignment help in an A/B test?

It makes the sample larger

It removes all random error

It balances other causes between groups in expectation

Which SQL feature gives a running total while keeping every row?

`SUM(x) OVER (ORDER BY day)`

`GROUP BY day`

`HAVING SUM(x) > 0`

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