# An example of the relationship between descriptive and inferential statistics

### Difference Between Descriptive and Inferential Statistics (with Comparison Chart) - Key Differences

The important point is that any statistic, inferential or descriptive, is a function For example the sample mean and standard deviation provide. Ex. Of randomly selected people in the town of Luserna, Italy, people had the last name Nicolussi. An example of descriptive statistics is the following. Difference between Descriptive and Inferential Statistics . For example, if we study the effectiveness of a new medication by comparing the outcomes in a.

Measures of central tendency: In this case, the frequency distribution is simply the distribution and pattern of marks scored by the students from the lowest to the highest.

## Descriptive and Inferential Statistics

We can describe this central position using a number of statistics, including the mode, median, and mean. You can read about measures of central tendency here. For example, the mean score of our students may be 65 out of However, not all students will have scored 65 marks. Rather, their scores will be spread out.

Some will be lower and others higher. Measures of spread help us to summarize how spread out these scores are.

To describe this spread, a number of statistics are available to us, including the range, quartiles, absolute deviation, variance and standard deviation. When we use descriptive statistics it is useful to summarize our group of data using a combination of tabulated description i. Join the 10,s of students, academics and professionals who rely on Laerd Statistics.

## Difference Between Descriptive and Inferential Statistics

For example, we could calculate the mean and standard deviation of the exam marks for the students and this could provide valuable information about this group of students.

Inferential Statistics is used to determine the probability of properties of the population on the basis of the properties of the sample, by employing probability theory.

Methods of inferential statistics: Estimation of parameters 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. The principle of describing or concluding also applies to the data or the collected information of the researcher.

Referring back to our earlier example about teenage pregnancies, descriptive statistics is only restricted to the population being described.

### What the relationship between descriptive and inferential statistics? | Socratic

In inferential statistics, X High School could just be a sample of the target population. Since it would be impossible to collect data from each high school in New York, X High School will then act as a sample that would reflect or represent all high schools in New York City.

Of course, this usually means that a margin of error is present, since one sample is not enough to represent the whole population.

This rate of possible error is also taken into account when analyzing the data. Using various calculations like mean, median, and mode, researchers would be able to describe or examine data and achieve what they want through the process. For example, launching inferential statistics on the rate of population growth in a particular city could serve as a basis for a business to decide whether or not to set up shop in that city.