A car manufacturing company releases a new car and it claims that the car has a mileage of 25 kms per liter. Should we believe it or not? And why should or shouldn't we believe it? Hypothesis testing is a method that can be used to make decisions in such situations.
Hypothesis testing generally involves four steps.
- First, we develop two claims: null hypothesis (H0) and alternative hypothesis (Ha). In our case ‘the car can run 20 kms per liter’ is a null hypothesis and ‘the car can’t run 20 kms per liter’ is an alternative hypothesis.
- Second, we collect a sample (sample of newly manufactures cars) and collect relevant data from them and summarize it using statistics.
- Then, we calculate how probable it is to find the result from our analysis if the hypothesis was true.
- Finally, we reach a conclusion based on our result in the previous step. If probability of the observed data is very low, we can safely discard our null hypothesis in favor of our alternative hypothesis. If it isn't low, we can continue to believe the null.
Thus, by using hypothesis testing we can evaluate mutually exclusive claims and choose the one which is best supported by our data.