python code for hypothesis testing

hypothesis testing is a statistical method used to make inferences about a population based on a sample of data. in this tutorial, we will cover the basics of hypothesis testing using python, focusing on the two-sample t-test as an example.
formulate hypotheses:
choose significance level (α):
collect and analyze data:
compute test statistic:
determine critical region:
make a decision:
draw conclusion:
let's assume we have two sets of exam scores for two different teaching methods, and we want to test if there is a significant difference in the mean scores.
remember to adapt this code to your specific scenario and datasets.
hypothesis testing is a powerful tool for drawing conclusions about populations based on sample data. python, with its rich ecosystem of statistical libraries, makes it easy to perform hypothesis tests and analyze the results. always remember to carefully formulate your hypotheses, choose an appropriate significance level, and interpret the results in the context of your study.
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