Python Functions for Statistical Applications

1A. Implementation with the standard def keyword

Suppose you have done a statistical comparison using the Z-scores approach. Write a function for calculating the lower bound of the 95% CI. A starter code for this function is already provided to you below.

def compute_lower_bound(n, mu, stdev, z=1.96): """ Computes lower bound of a confidence interval Parameters: n: Type int. number of data points mu: Type float. sample mean stdev: Type float. sample standard deviation z: Type float. critical value. Default to 95%CI that corresponds to value of 1.96 """ # YOUR CODE HERE # Hint: A correct implementation can be as short as just 1 line long!

1B. Using the function of Part 1A

Run your function on the following scenario:

There are 500 data points.

The sample mean is 2525

The sample standard deviation is 7.57.5

The critical value at 95% confidence, 0.950.95, is a constant: 1.96

# YOUR CODE HERE

1C. Application of Part 1A

Now, you are asked to do the same computation as above, except for 99% CI now.

Hints:

Make a change to the function call, not the function itself

Consider Googl'ing the "99% confidence interval"

# YOUR CODE HERE