P-values help determine the strength of evidence against the null hypothesis in hypothesis testing. A p-value represents the probability of obtaining a test statistic as extreme as, or more extreme than, the observed value, assuming the null hypothesis is true. Here's an example code snippet for performing a t-test and obtaining the p-value:
import scipy.stats as stats
# Assuming we have two arrays `sample1` and `sample2` for comparison
t_statistic, p_value = stats.ttest_ind(sample1, sample2)
print("T-Statistic:", t_statistic)
print("P-Value:", p_value)
