Hypothesis testing: An explanation

This paperdeals with a statistical method‘hypothesis testing’. In the methodology of hypothesis testing, required information is gathered from a random sample collected from a certain population which requires to be analyzed. This ‘sample’ information is subjected to suitable statistical investigation and assessment after which, the results are cautiously extended to generalize about the population from which the sample was gathered. Hence, hypothesis testing is a basic and essential process to make a suitable inferential decision about population of interest to the researcher.

Hypothesis testing, therefore, is to be understood as an essential and necessary procedure in statistics. A hypothesis test weighs and assesses two mutually exclusive statements about a population under examination in order to determine which of these two statements are best described and supported by the sample data. When it is inferred about the sample data that it is ‘statistically significant’, we want to actually know what exactly this signifies about the population. We also are interested in knowing how these tests work practically and what their usefulness is in real world and further, what does‘statistical significance’ actually mean? The paper would help to intuitively understand how hypotheses tests are applied in practical situations by focusing more on concepts rather than on formulae, equations and numbers.