Course Content
Learning Statistics with Python
Performing a t-test in Python
To perform a t-test in Python, you only need to choose the alternative hypothesis and whether variances are homogeneous(roughly equal).
The ttest_ind()
function from scipy.stats
takes care of everything else. Here is its syntax:
Parameters:
a
— first sample;b
— second sample;equal_var
— setTrue
if variances are roughly equal andFalse
if they aren't;alternative
— type of alternative hypothesis:'two-sided'
— means are not equal;'less'
— the first mean is less than the second;'greater'
— the first mean is greater than the second.
Returns:
statistic
— the value of t statistic;pvalue
— the p-value.
We are interested in the pvalue
. If it is lower than α(usually 0.05), then the t statistic is in the critical region, so we should accept the alternative hypothesis. And if pvalue
is greater than α — we accept the null hypothesis that means are equal.
Here an example of applying t-test to our heights dataset:
Section 6.
Chapter 6