Explore the implications of non-linear patterns in scatter plots within the realm of Business Intelligence and their impact on data analysis.

Learn how to create, interpret, and communicate with scatter plots, which are graphs that show the relationship between two variables in research data.

A linear relationship (or linear association) is a statistical term used to describe the directly proportional relationship between a variable and a constant.

Figure 2: Examples of scatter plots where the relationship between the outcome and explanatory variables takes both linear and non-linear shapes. Credit: Technology Networks.

Scatter Plot with Linear Regression This application displays a scatter plot and fits a linear regression line to the data using a server-side API. The user can upload a CSV file containing the data ...

Pearson’s correlation helps us understand the relationship between two quantitative variables when the relationship between them is assumed to take a linear pattern. The relationship between two ...

A positive correlation on a scatter plot is evidenced by an upward-trending series of points that show that as the x-axis variable increases, so does the y-axis variable.

Scatter Plot with Linear Regression This application displays a scatter plot and fits a linear regression line to the data using a server-side API. The user can upload a CSV file containing the data ...