Question

Consider the different impacts that these two aspects of statistics will have on your role as an engineer. 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

Answer 1

Answer:

Check the explanation

Step-by-step explanation:

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, organised, 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 summaries 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.

Answer 2

Answer:

The question is incomplete, the complementary part is left on the graph and the requested ones are answered

Differences between inferential and descriptive statistics:

1. We know that in descriptive statistics the main objective is only to describe data from the population, in inferential what is sought is to analyze data to draw conclusions from them

2. In descriptive statistics, the process involves collecting information, organizing it, and displaying data that are relevant or significant. In inferential statistics, the data is taken and processed to evaluate hypotheses and draw conclusions regarding future results.

3. the representation in the descriptive statistics is made by means of diagrams or tabulations and the result in the inferential one is given in probability

4. When we have a situation, descriptive statistics allows us to describe it and, in inferential, we obtain the probability that the event will occur.

descriptive statistics is based on known data, inferential it is intended to project future situations, which allows with all the previous answers to generate an important panorama for the development of engineering and its true application in a real field

-. an example is the following

Of 350 people taken at random in Madrid, Spain, 280 had the surname Martinez, we can take this situation to the descriptive statistic as follows:

80% of people carry the surname Martinez

We have, then, the result of a small sample of a city, not of the entire population of Spain, so the result has been generalized and we refer to a country from a small sample, however we must verify it and take it to a statistic inferential