What is hypothesis test?

 Hypothesis tests are statistical procedures used to determine whether an observed effect or relationship between variables is statistically significant or if it could have occurred by chance.

The process of hypothesis testing involves the following steps:

  1. State the null hypothesis (H0) and the alternative hypothesis (Ha or H1) based on the research question.

  2. Choose a level of significance (alpha) to determine the probability of making a type I error (rejecting the null hypothesis when it is actually true).

  3. Collect data and compute a test statistic, which measures the degree of difference or relationship between the variables.

  4. Determine the p-value, which is the probability of obtaining a test statistic as extreme or more extreme than the observed value, assuming the null hypothesis is true.

  5. Compare the p-value with the chosen level of significance. If the p-value is less than the level of significance, reject the null hypothesis and accept the alternative hypothesis. If the p-value is greater than or equal to the level of significance, fail to reject the null hypothesis.

  6. Interpret the results and draw conclusions based on the findings.

Hypothesis tests can be used to compare means, proportions, variances, and other statistical measures. They are commonly used in scientific research, business, healthcare, and other fields to make informed decisions and draw meaningful conclusions from data.

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