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# Scatter plots

Scatter plots are visualizations of two variables like X and Y. They are a fundamental tool in statistial disciplines as the regression analysis. Scatter plots help visualizing the relationship between X and Y which is the main objective in regression analysis.

## Scatter plots example

Say we wish to visualize the relation between property prices and year. Let’s take the period of the financial crisis starting in 2008.  X is the independent variable (year) and Y the dependent variable (price):

The regression analysis is a so-called bivariate analysis because it has two variables (X and Y). Through the regression analysis we can explore the correlation between Y is of X. In our example, we discover how dependent the property prices are based on the variation in year.

The scatter plot graph can answer to questions like these:

• how much does price (Y) vary from year 2008 to 2010 (X)?
• Is there correlation between the property prices (Y) and year (X)?
• How does property price (Y) change as year (X) changes?

## Types of correlation

While scatter plots expose the association between the X and Y, they do not describe the relation in cause and effect. Example of different types of correlation between X and Y:

## Direction, strength and linearity

Let’s hand draw an approximated trendline or a regression line and qualify this line as to its direction, strength and linearity which are terms often applied in statistical analysis:

In regression line and in most of the chapters related to regression analysis, we go apply the scatter plots for varies different purposes.

## Learning statistics

#### Carsten Grube

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##### ANOVA & the F-distribution

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