# Tag Archives: stat

# ECDFs stat Empirical cumulative distribution functions

In this exercise, you will write a function that takes as input a 1D array of data and then returns the `x`

and `y`

values of the ECDF. ECDFs are among the most important plots in statistical analysis. You can write your own function, `foo(x,y)`

according to the following skeleton:

```
def foo(a,b):
"""State what function does here"""
# Computation performed here
return x, y
```

The function `foo()`

above takes two arguments `a`

and `b`

and returns two values `x`

and `y`

. The function header `def foo(a,b):`

contains the function signature`foo(a,b)`

, which consists of the function name, along with its parameters.

Define a function with the signature `ecdf(data)`

. Within the function definition,

- Compute the number of data points,
`n`

, using the`len()`

function. - The xx-values are the sorted data. Use the
`np.sort()`

function to perform the sorting. - The yy data of the ECDF go from
`1/n`

to`1`

in equally spaced increments. You can construct this using`np.arange()`

and then dividing by`n`

. - The function returns the values
`x`

and`y`

.

def ecdf(data): """Compute ECDF for a one-dimensional array of measurements.""" # Number of data points: n n=len(data) # x-data for the ECDF: x x=np.sort(data) # y-data for the ECDF: y y=np.arange(1,n+1)/n return x, y