{"id":249316,"date":"2024-04-01T13:24:14","date_gmt":"2024-04-01T13:24:14","guid":{"rendered":"https:\/\/namso-gen.co\/blog\/?p=249316"},"modified":"2024-04-01T13:24:14","modified_gmt":"2024-04-01T13:24:14","slug":"what-does-p-value-mean-in-2-sample-t-test","status":"publish","type":"post","link":"https:\/\/namso-gen.co\/blog\/what-does-p-value-mean-in-2-sample-t-test\/","title":{"rendered":"What does p-value mean in 2 sample t-test?"},"content":{"rendered":"

The p-value is a crucial statistical measure in the domain of hypothesis testing, particularly in the context of a 2 sample t-test. In statistical hypothesis testing, researchers aim to make inferences about a population based on sample data. The p-value helps determine the strength of evidence against the null hypothesis, which assumes that there is no significant difference between the two groups being compared. It quantifies the probability of obtaining the observed sample results, or results more extreme, under the assumption that the null hypothesis is true. In other words, the p-value allows us to evaluate whether the observed data is statistically significant or merely due to chance.<\/p>\n

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