python-scipyHow can I use Python and SciPy to perform a hypothesis test?

You can use Python and SciPy to perform a hypothesis test by first defining the null and alternative hypotheses. The null hypothesis is the initial claim that you are trying to test, while the alternative hypothesis is the claim that you are trying to prove.

Once the hypotheses are defined, you can use SciPy's stats module to run the appropriate statistical test. For example, if you wanted to run a two-tailed t-test, you could use the ttest_ind function from SciPy's stats module, like so:

from scipy import stats

stat, p = stats.ttest_ind(data1, data2)
print('stat=%.3f, p=%.3f' % (stat, p))

Output example

stat=2.531, p=0.012

The ttest_ind function takes two data sets as arguments and returns the t-statistic and the p-value. The p-value indicates the probability of getting a result at least as extreme as the one observed, if the null hypothesis is true. If the p-value is less than the significance level (usually 0.05), then the null hypothesis can be rejected and the alternative hypothesis can be accepted.

For more information, see the following links:

• SciPy Documentation for stats module
• Hypothesis Testing with SciPy

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