Question

First, we are measuring things using data. The basic bit of data is the variable. These come in two "flavors" - discrete and continuous. What are the differences between these two types? How might measuring them differ? And we collect the data often using sampling so, given all of the different methods of sampling designs, why is using a random collection (sampling) method so important?

Answer 1

Answer:

Significance of irregular assortment i.e., Sampling technique :

It is the simplicity of amassing the example.

It is likewise considered as a reasonable method for choosing an example from a given populace since each part is given equivalent chances of being chosen.

Continuous variable:

A variable taking every single imaginable incentive in a specific range is called as nonstop factor.

Models:

Weight of an individual, length of a screw which is delivered by a machine.

Discrete variable:

A variable taking just specific worth is called discrete variable.

Models:

Number of understudies in a class, number of articles delivered by a machine.

Here the discrete factors are the factors wherein the can be gotten by depending on other hand , ceaseless factors are the irregular factors that estimates something.