Array mean and std

Compute the mean and population standard deviation of a list of numbers.

statistics mean std math

Write a function `array_stats(nums)` that takes a list of numbers (integers or floats) and returns a tuple `(mean, std)` where:  - `mean` is the arithmetic average of the numbers, rounded to 3 decimal places (use Python's round, which rounds half to even).  - `std` is the population standard deviation (divide by n, not n-1), also rounded to 3 decimal places. If the list is empty, return `(0.0, 0.0)`. The function must always return floats even if the input contains only integers.  For example, `array_stats([2, 4, 4, 4, 5, 5, 7, 9])` should return `(5.0, 2.0)`. Note: the population standard deviation is the square root of the average of squared deviations from the mean.

Constraints

The input list length is between 0 and 10^5. Numbers are finite real numbers. The result will fit within Python's floating-point precision. The time complexity should be O(n).

Example

>>> array_stats([2, 4, 4, 4, 5, 5, 7, 9])
(5.0, 2.0)
>>> array_stats([10, 20, 30])
(20.0, 8.165)
>>> array_stats([])
(0.0, 0.0)

10 points ~15 min

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Hints

Calculate the mean first, then compute the average of squared differences from that mean.

Use math.sqrt for the square root, but remember to round to 3 decimals only at the end.

For an empty list, detect it early and return (0.0, 0.0).

The population standard deviation divides by n, not n-1.

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