I am following stats courses at the moment and I am a bit confused about performing a t-test. I know that a t-test assumes normality and enough sample size. In the course I am attending, the instructor is performing a t-test on the following samples:
a = np.array([0.28, 0.97, 1.25, 2.46, 2.51, 1.17, 1.78, 1.21, 1.63, 1.98])
b = np.array ([2.36,2.11, 0.45, 1.76, 2.09, 1.5 , 1.25, 0.72, 0.42, 1.53])
Are the samples big enough to perform a t-test? When I tried to plot histogram for both datasets it doesn`t seem they are normally distributed.
Another approach I have seen when making a test for the mean is drawing bootstrap samples. In which scenarios I make bootstrap replicates and in which I can directly make the t test?