Discuss how these two branches of statistics will provide different capabilities and impacts in your engineering discipline. Provide an example of an area where you might use descriptive statistics to better understand a variable, as well as an example of an area where inferential statistics might be needed to draw some conclusion from a set of variables data that you have. Do you see both descriptive and inferential statistics being necessary for your future success as an engineer? Explain your reasons for that opinion.

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Mathematics

Walter

26 March, 01:55

Discuss how these two branches of statistics will provide different capabilities and impacts in your engineering discipline. Provide an example of an area where you might use descriptive statistics to better understand a variable, as well as an example of an area where inferential statistics might be needed to draw some conclusion from a set of variables data that you have. Do you see both descriptive and inferential statistics being necessary for your future success as an engineer? Explain your reasons for that opinion.

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Jethro · Answer 1

Key Differences Between Descriptive and Inferential Statistics:

The difference between descriptive and inferential statistics can be drawn clearly on the following grounds:

Descriptive Statistics is a discipline which is concerned with describing the population under study. Inferential Statistics is a type of statistics; that focuses on drawing conclusions about the population, on the basis of sample analysis and observation.

Descriptive Statistics collects, organises, analyzes and presents data in a meaningful way. On the contrary, Inferential Statistics, compares data, test hypothesis and make predictions of the future outcomes.

There is a diagrammatic or tabular representation of final result in descriptive statistics whereas the final result is displayed in the form of probability.

Descriptive statistics describes a situation while inferential statistics explains the likelihood of the occurrence of an event.

Descriptive statistics explains the data, which is already known, to summarise sample. Conversely, inferential statistics attempts to reach the conclusion to learn about the population; that extends beyond the data available.

Ex. Of 350 randomly selected people in the town of Luserna, Italy, 280 people had the last name Nicolussi. An example of descriptive statistics is the following statement:

"80% of these people have the last name Nicolussi."

Ex. Of 350 randomly selected people in the town of Luserna, Italy, 280 people had the last name Nicolussi. An example of inferential statistics is the following statement:

"80% of all people living in Italy have the last name Nicolussi."

We have no information about all people living in Italy, just about the 350 living in Luserna. We have taken that information and generalized it to talk about all people living in Italy. The easiest way to tell that this statement is not descriptive is by trying to verify it based upon the information provided.