The main objective in statistics is testing a hypothesis. For example, you could conduct a test to find either a drug is effective or not for treating headaches. If you repeat the experiment then no one would take the results seriously. A hypothesis is an educated guess that analyze the things around you and it could be tested either through some experiment or observation. For example –

- A new medicine may work or not.
- Find the best style for educating the audience in a better way.
- Find the location of new species too.
- Find a satisfactory style to administer the standardized tests.
- The output could be anything as soon as you put the values in the test.

If you wanted to propose a hypothesis then this is necessary to write a statement first and it should be well explained to understand the circumstances. A good statement always includes If and then statements. It involves both independent or dependent variables. It should be based on research or data collected earlier.

The statement must have specific design criteria that could suit the engineering or programming projects perfectly. The hypothesis testing formula in mathematics is given as below –

\[\large z=\frac{\overline{x}-\mu }{\frac{\sigma }{\sqrt{n}}}\]

Where,

$\overline{x}$ is the sample mean

$\mu$ is the population mean

$\sigma$ is the standard deviation and *n* is the sample size.

Hypothesis testing in statistics helps you to identify either result of a survey or experiment is meaningful or not. You can also check either your results find out the odds that happened by chance only. The experiments that has to repeat, they are of little use only. The concept could be confusing in beginning but a depth understanding always gives you the accurate results.