When a graph does not show any clear trends, it likely indicates that the variables are either unrelated or have a weak correlation. This lack of a discernible pattern suggests that changes in one variable do not consistently affect the other. Additionally, it may imply that other confounding factors are influencing the relationship between the variables.
there is a strong relationship between the variables
there is no solution
Any variables can be shown on a graph.
The best type of graph to show continuous data is a line graph. Line graphs effectively display trends over time or other continuous variables, allowing for easy visualization of changes and patterns. They connect individual data points with lines, making it clear how values fluctuate within the dataset.
There are a few graphs for that but probably the most common and best one is a Line Graph or a Bar Chart.
there is a strong relationship between the variables
there is no solution
You could probably do wins by length by width
No correlation. Answer provided by
Any variables can be shown on a graph.
Normally, only two variables are assigned to a table graph, one for each axis. You can, however, extend the variables included in a graph by using the box color as an indicator, although this is abnormal and may become confusing and as such its probably best to stick with two variables, an independent and dependent variable.
no correalation
The best type of graph to show continuous data is a line graph. Line graphs effectively display trends over time or other continuous variables, allowing for easy visualization of changes and patterns. They connect individual data points with lines, making it clear how values fluctuate within the dataset.
A rather random zig-zag, probably.
Probably where both variables are continuous.
There are a few graphs for that but probably the most common and best one is a Line Graph or a Bar Chart.
A diagram that shows how two variables are related is called a "scatter plot." It is a visual representation of the relationship between the two variables, often used to identify patterns or trends in the data.