![]() The lower a P-value, the stronger the evidence.Īs a conclusion, the larger the absolute value of the test statistic, the smaller the p-value, and the greater the evidence against the null hypothesis. Therefore, a P-value that is less than 0.05, indicates strong evidence against the null hypothesis, so you reject the null hypothesis. P-value is the level of marginal significance within a statistical hypothesis test, representing the probability of the occurrence of a given event. Other than test statistic, P-value is another important result to look at. If the test statistic ≤ critical value, the null hypothesis is accepted.If the test statistic > critical value, the null hypothesis is rejected.The critical values are the boundaries of the critical region. This test-statistic is then compared with a critical value. ![]() A null hypothesis (H0) proposes that no significant difference exists in a set of given observations, and an alternative hypothesis (H1) proposes otherwise.įor rejecting a null hypothesis, a test statistic is calculated. Next, you will be deciding on the hypothesis based on your test objective. To validate whether there’s a relationship between 2 categorical variables.To compare the difference between 2 groups of data to see whether the difference is statistically significant.To validate whether the population mean is correct.Get all the statistical tests clear in 3 minutes! The Question to be Answeredīefore we decide on which test to use, we need to be clear of what we want to solve. ![]() ![]() Which Statistical Test to Use? Follow This Cheat Sheet ![]()
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