What is the difference between hypothesis testing and point estimation?

What will be an ideal response?

Hypothesis testing. Many empirical claims can be translated into specific statements about a population that can be confirmed or disconfirmed with the aid of probability theory. To take a simple example, the assertion that there is no gender gap in American politics can be restated as “Hypothesis: men’s mean liberalism scores equal women’s mean liberalism scores.” One way to test this hypothesis is by measuring the difference between the mean responses among men and women. If the difference is in the expected direction, and statistically significant, we can accept the hypothesis: point and interval estimation. The goal here is to estimate unknown population parameters from samples and to surround those estimates with confidence intervals. Confidence intervals suggest the estimate’s reliability or precision.