What is a Scatter Diagram (Correlation Chart)?
The scatter diagram is used to find the correlation between these two variables. This type of diagram is also known as Scatter Diagram with Negative Slant. Scatter plots are similar to line graphs in that they use horizontal and vertical axes to The relationship between two variables is called their correlation. y- axis down to a high-value on the x-axis, the variables have a negative correlation . Scatter Plot (also called scatter diagram) is used to investigate the possible relationship between two variables that both relate to the same event. If the points cluster in a band from upper left to lower right, there is a negative correlation (if x.
What is a Scatter Diagram (Correlation Chart)?
Once the diagram is completed, you notice that as the speed of vehicle increases, the number of accidents also goes up. This shows that there is a relationship between the speed of vehicles and accidents happening on the highway. Scatter diagrams can demonstrate a relationship between any element of a process, environment, or activity on one axis and a quality defect on the other axis. Usually the independent variable is plotted along the horizontal axis x-axis and the dependent variable is plotted on the vertical axis y-axis.
The independent variable is also known as the control parameter because it influences the behavior of the dependent variable. It is not necessary for one parameter to be a controlling parameter. You can draw the scatter diagram with both variables independent to each other.
In this case you can draw any variable on any axis. Please note that the scatter diagram is different than the Ishikawa or fishbone diagram. With the Ishikawa diagram you see the effect of a cause, and in the scatter diagram you analyze the relationship between the two variables. Type of Scatter Diagram The scatter diagram can be categorized into several types; however, I will discuss the two types that will cover most scatter diagrams used in project management. The first type is based on the type of correlation, and the second type is based on the slope of trend.
According to the type of correlation, scatter diagrams can be divided into following categories: In this type of scatter diagram, data points are spread so randomly that you cannot draw any line through them. In this case you can say that there is no relation between these two variables.
Here, the data points are little closer together and you can feel that some kind of relation exists between these two variables. In this diagram, data points are grouped very close to each other such that you can draw a line by following their pattern. In this case you will say that the variables are closely related to each other.
As discussed earlier, you can also divide the scatter diagram according to the slope, or trend, of the data points: Scatter Diagram with Strong Positive Correlation Scatter Diagram with Weak Positive Correlation Scatter Diagram with Strong Negative Correlation Scatter Diagram with Weak Negative Correlation Scatter Diagram with Weakest or no Correlation Strong positive correlation means there is a clearly visible upward trend from left to right; a strong negative correlation means there is a clearly visible downward trend from left to right.
Scatterplots and correlation review (article) | Khan Academy
A weak correlation means the trend, up of down, is less clear. A flat line from left to right is the weakest correlation, as it is neither positive nor negative and indicates the independent variable does not affect the dependent variable.
In positive slant, the correlation will be positive, i.
You can say that the slope of straight line drawn along the data points will go up. The pattern will resemble the straight line. For example, if the temperature goes up, cold drink sales will also go up. Scatter Diagram with Weak Positive Correlation Here as the value of x increases the value of y will also tend to increase, but the pattern will not closely resemble a straight line. In negative slant, the correlation will be negative, i. The slope of a straight line drawn along the data points will go down.
For example, if the temperature goes up, sales of winter coats goes down. Scatter Diagram with Weak Negative Correlation Here as the value of x increases the value of y will tend to decrease, but the pattern will not be as well defined. Scatter Diagram with no Correlation In this type of chart, you are not able to see any kind of relationship between the two variables.
In either case, the independent variable has no effect on the second variable it is not dependent. However, they have a very specific purpose. Scatter plots show how much one variable is affected by another. The relationship between two variables is called their correlation. Scatter plots usually consist of a large body of data. The closer the data points come when plotted to making a straight line, the higher the correlation between the two variables, or the stronger the relationship.
If the data points make a straight line going from the origin out to high x- and y-values, then the variables are said to have a positive correlation. If the line goes from a high-value on the y-axis down to a high-value on the x-axis, the variables have a negative correlation. A perfect positive correlation is given the value of 1. A perfect negative correlation is given the value of If there is absolutely no correlation present the value given is 0. The closer the number is to 1 or -1, the stronger the correlation, or the stronger the relationship between the variables.
The closer the number is to 0, the weaker the correlation.