Inferential statistics is a study of various procedures that are applied to conclude from the characteristics of a large group of data and that large group of data is known as population. Inferential statistics deliver answers about population related questions and it also tries to respond about those samples that are obtained from within the population and never been tested.

Inferential statistics is based on probability, every sample has a probability of more than one inference. If proper preparations will be made to conduct an experiment, then there will be an improvement in the obtained inferences.

There are various models of inferential statistics that improved the analysis process. Selection of model for every experiment depends on the requirements of particular experiment. For best results select a models with care. If proper attention is not given during the selection of the model, then the errors could give wrong inference about the present experiment.

## Example

An experiment is being conducted on the last three Mondays, Ali sold 5, 3 and 2 nokia mobile phones respectively. An example of **inferential statistics** in that experiment are the following statements:

- “Ali never sells more than 5 mobiles on a Monday.”
- “Ali sells at least two mobiles on a Monday.”

This statement is true for these three Mondays, but it will not always be true for every monday.