This module contains some useful functions for doing simple statistics with your data, like calculating means, medians, quantiles and confidence intervals.
Returns the mean of data, which has to be a list or a tuple.
Calculates the variance of data. Take its square root if you need the standard deviation.
Returns both the mean and the variance. It’s slightly faster than calculating them separately and is preferable if you need them both:
mean, var = mean_var(data)
This functions returns the mean and the standard error of the sample.
Returns the mean of the sample data and half its confidence interval width, meaning if the resulting values are mean and ci, then the confidence interval is actually [mean - ci, mean + ci],
Returns the median of the sample.
Returns one or more quantiles of data. If q is a single number, the result will also be just the value of the requested quantile. q can also be a list or a tuple with several quantiles; in this case the return value is a list with corresponding values from data. If you need more than one quantile for a sample, choose the list way over calculating them repeatedly, as this will be faster for large samples.
This function calculates the inverse cumulative density function of the standard normal distribution. Useful when you need to know the factor to multiply the standard deviation with to get a certain confidence interval. For example, for a two-sided mean confidence interval of 95%, the factor is:
f = stdnorm_invcdf(0.975) # about 1.96