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Regression analysis or linear regression is one of the most commonly used technique in all the applications of statistics.
In the regression analysis, one can create linear relationships between two or more variables. These relationships are then tested by measuring the correlation between these variables.

There are some scenarios that make regression analysis more effective than other statistical analysis, such as if you want to study the relationship between two variables that are not direct, you need to use statistical regression analysis.

Regression Analysis has three different categories:

Partial regression analysis

Correlation analysis

Principal component analysis

These three categories of regression analysis will be explained in this tutorial.

Understanding regression analysis:

Regression analysis is a part of the applied statistics and this technique is used to measure the relationship between two or more independent variables with one dependent variable.

There are three different categories of regression analysis:

Partial regression analysis

Correlation analysis

Principal component analysis

Let’s see the above-mentioned categories of regression analysis:

Partial regression analysis:

Partial regression analysis is one of the most frequently used regression analysis techniques that are mostly applied in Economics, Marketing, and other business.
In the partial regression analysis, we are measuring the relationship between two independent variables with one dependent variable.

For example, we may wish to study the relationship between the television shows that people watch and the shows that they like.
Therefore, we may make the following observations:

People usually watch the television shows that they like;

A person might be more likely to watch the television show that they like;

These two observations indicate that the television show that a person likes is likely to be watched by that person;

However, one observation might not be sufficient to draw any conclusions about the other observation.

To avoid this limitation, we should always add more observations into the regression analysis.
The addition of other observations helps us draw better conclusions and gives us the advantage of having more data to work with.

In addition, we can also use the partial regression analysis to determine the relationship between two or more independent variables with one dependent variable.

The limitations of partial regression analysis:

The limitations of partial regression analysis are that it only allows us to study the relationship between two or more independent variables with one dependent variable.

Partial regression analysis is not effective if the independent variable is not significant, which means it has no effect on eea19f52d2

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