Question

• How is it that we are able to select data sets from a larger population and draw reasonable inferences from the data sets about the larger population? What is statistical inference all about? Explain and discuss.

Answer 1

Data sets are selected from larger populations by using clustering or sections of population which are based on a defining characteristic. The clusters or samples of a larger population base are based on several attributes in order to bring uniformity within groups.

As the groups are thus differentiated, one is able to draw reasonable inferences from the data sets about the larger population whether a specific factor has had an implied effect.

There is also a control group and an experimental group maintained. Whereby data sets from the larger population base are included in a particular experiment. Whereas the other data set is not experimented upon and thus is in the control group. Thus there are several ways to achieve reasonable inferences from the data sets in order to garner effective results.

Statistical inference is all about taking samples from a large population base, performing hypothesis testing regarding whether a particular phenomenon or inference can be drawn from the population sample. Then showcasing conclusions based on the sample inference. And then generalizing to the entire population base whereby the idea is applicable to the entire population base.

For example, sample is selected from poor economic backgrounds, who earn less than a certain amount. Some amount of transfer payments are performed on the sample and inference is drawn based on the sample's, whether it benefited the sample groups. Then the study is applied to the general population on a larger scale based on the initial statistical inference.