A scatter plot can be used either when one continuous variable that is under the control of the experimenter and the other depends on it or when both continuous variables are independent. If a parameter exists that is systematically incremented and/or decremented by the other, it is called the control parameter or independent value and is plotted along the horizontal axis. The measured is customarily plotted along the vertical axis. A trendline or a line of best fit can be drawn in order to study the relationship between the variables. An equation for the correlation between the variables can be determined by established best-fit procedures. For a linear correlation, the best-fit procedure is known as linear regression. A simple linear regression is a model which explains a single variable. In this case weight & height. It shows the correlations between the weight compared to the height of 10 yr old boys. The linear regression of this scatter plot shows that it can be predicted that as the boy’s height increases the weight will in most cases increase.
y=1.3022x + 4.5792 (r2=.8849)
In my scatter plot my r value = 1.142103323.
Scatter plots can be used for various purposes. An important use for scatter plots and linear regressions is for predictions. You can also use it for monitoring daily blood pressures in patients, keep track of classroom grade averages within the class. When using scatter plots it indicates the changes in values, whether there is an increase or a decrease of the variables.