Hypothesis Testing
A hypothesis is a social theory about an event or a phenomenon that might be true or not. In science, conclusions about the world can be made by observing and taking measurements of different kind of things. In statistics, informed decisions can be made from the measurements in terms of hypotheses. Therefore, hypothesis testing is the procedure of determining whether a hypothesis is viable or not. Under hypothesis testing, there is a null hypothesis which implies that observations from a particular sample result from chance. On the other hand, alternative hypothesis states that sample observations are caused by a non-random cause. The two kinds of hypothesis are mutually exclusive in that when one is true, the next is false.
An example of a null hypothesis can be, majority of the students score an average of 70 marks in Mathematics. Evidence to support the null hypothesis can be measured using the p-value which is calculated using a value of a test static such as a t-test. When the p-value is greater than the significance level, there is enough evidence to support the null hypothesis that that many students score above 70 marks. When the p-value is calculated to be smaller than the significance level, the hypothesis that majority of the students score above 70 marks is not supported. Hypothesis testing is, therefore, vital in proving or disapproving informed or non-informed guesses about populations.