Descriptive vs. Inferential Statistics
Difference between Descriptive and Inferential Statistics: – There are two major fields within Statistics, and people often may feel confused about what the difference is between the two. Each of them is important and pursues different goals. These fields are known as Descriptive Statistics and Differential Statistics.
Difference between Descriptive and Inferential Statistics
If you have doubts about it or want more information about the difference between Descriptive and Inferential Statistics, read on, because here we explain the difference between Inferential Statistics and Descriptive Statistics.
This is the best known by most and as its name implies, its aim is to describe. In this case, numerical measures are used to analyze data and draw conclusions from them.
There are some elements and categories that belong specifically to this field of Statistics, such as:
The average: or measure of central tendency that results from the calculation of the sum of all the data of a variable divided by the number of data that contains the same.
Dispersion: has to do with the distance or difference between each value of the variable and the average of the same.
- Measurement of asymmetry and kurtosis.
- Exploration of relation and correlation between datasets.
- Presentations of statistical results in the form of graphs.
This area of statistics is responsible for the study of statistical samples. From the analysis of these samples, Inferential Statistics can infer, estimate or draw conclusions from the sample of a population. In turn, Inferential Statistics is divided into two major groups, which are:
- The estimation of confidence intervals: is a range of values for an unknown parameter through the measurement of the sample taken from a population.
- Proof of Significance or Hypothesis Test: this consists of testing the claims made about a population from the sample size.
In short, the difference between Descriptive Statistics and Inferential Statistics is that the former is only responsible for making descriptions from certain data; while the second goes further and makes estimates about the data collected from samples taken from a population.