# Are used to show the relationship between two factors

### What is a Scatter Diagram (Correlation Chart)?

used to measure the strength and direction of the linear relationship, of one factor, X, will show some pattern or relationship with values of a second factor, Y. there is no relationship between two factors (a zero correlation) in the population. Ideally a mapping, or a scatter victoryawards.us a function because it should not map one value to many (eg square root).Not the regression coefficient since for an even. The other technique that is often used in these circumstances is regression, which Complete correlation between two variables is expressed by either + 1 or of observations and wishes to see whether there is a relationship between.

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.

## Describing scatterplots (form, direction, strength, outliers)

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.

• What is a Scatter Plot?
• Making and describing scatterplots
• When to Use Scatter Plots

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.

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.

### Describing scatterplots (form, direction, strength, outliers) (article) | Khan Academy

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. Limitations of a Scatter Diagram The following are a few limitations of a scatter diagram: Scatter diagrams are unable to give you the exact extent of correlation.

Pearson Correlation - SPSS

Scatter diagram does not show you the quantitative measure of the relationship between the variable. It only shows the quantitative expression of the quantitative change. This chart does not show you the relationship for more than two variables.

Benefits of a Scatter Diagram The following are a few advantages of a scatter diagram: It shows the relationship between two variables. So something that seems to kind of correlate in a positive direction might have a value of 0. An example of a situation where you might find a perfect positive correlation, as we have in the graph on the left above, would be when you compare the total amount of money spent on tickets at the movie theater with the number of people who go.

This means that every time that "x" number of people go, "y" amount of money is spent on tickets without variation. An example of a situation where you might find a perfect negative correlation, as in the graph on the right above, would be if you were comparing the amount of time it takes to reach a destination with the distance of a car traveling at constant speed from that destination.

On the other hand, a situation where you might find a strong but not perfect positive correlation would be if you examined the number of hours students spent studying for an exam versus the grade received.

### What is used to show the relationship between two factors

This won't be a perfect correlation because two people could spend the same amount of time studying and get different grades. But in general the rule will hold true that as the amount of time studying increases so does the grade received. Let's take a look at some examples. The graphs that were shown above each had a perfect correlation, so their values were 1 and The graphs below obviously do not have perfect correlations.

Which graph would have a correlation of 0? Click on Answers when you think that you have them all matched up.