Plotly scatter plot matrix how to interpret
How to interpret a scatter plot
Scatter plots are useful for developing statistical data to be interpreted. Each observation (or point) on a scatter plot has two coordinates - the first corresponds to the first part of the data in the pair (that is, the X Coordinates- the amount you move left or right). The second corresponds to the second part of the data in the coordinate pair (that's the Y-Coordinates- the amount you go up or down). The point that represents the observation is placed at the intersection of the two coordinates.
The above illustration shows a scatter plot for the temperature and cricket chirps data listed in the table below.
|Temperature data and cricket chirps (excerpt)|
|Temperature (Fahrenheit)||Number of chirps (in 15 seconds)|
As the data ordered according to their XValues correspond to the points on the scatter plot from left to right to the observations given in the table in the order listed.
You interpret a scatter plot to look for trends in the data as you go from left to right:
If the data shows a hopeless pattern as you move from left to right, that indicates it positive relationship between X and Y. because the XIncrease values (to the right) that Y- Values are usually to be increased (upwards).
If the data shows a downhill pattern of moving left to right, that suggests it negative relationship between X and Y. because the X-valuesincrease (move right) die Y- Values are usually to be reduced (downwards).
If the data doesn't seem to resemble any type of pattern (even a vague one) then there is no relationship between X and Y.
One pattern of particular interest is one linear Pattern in which the data has a general appearance of a line going uphill or downhill. Looking at the previous figure, you can see that a positive linear relationship is displayed between the temperature and the number of crickets chirps. That said, when the temperature rises, the number of cricket chirps also rises. Note that the scatter plot suggests only a linear relationship between the two sets of values. It does Not suggest an increase in temperature causes the number of crickets chirps to increase.
A linear relationship between X and Y is when the pattern of the X- and Y-Values is like a line, either uphill (with a positive slope) or down (with a negative slope).
Scatter plots show possible associations or relationships between two variables. However, just because your diagram or graph is showing something does not mean that there is a cause and effect relationship.
For example, a doctor observes that people who take vitamin C every day seem to have fewer colds. Does this mean vitamin C prevents colds? Not necessarily. It could be that people who take more health every day are aware of vitamin C, but they also eat healthier, are not overweight, exercise every day, and wash their hands, often more. If this doctor really wants to know if it is the vitamin C that it does, she needs a well-designed experiment that rules out these factors.
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