<P> A scatter plot can suggest various kinds of correlations between variables with a certain confidence interval . For example , weight and height , weight would be on y axis and height would be on the x axis . Correlations may be positive ( rising ) , negative ( falling ) , or null ( uncorrelated ) . If the pattern of dots slopes from lower left to upper right , it indicates a positive correlation between the variables being studied . If the pattern of dots slopes from upper left to lower right , it indicates a negative correlation . A line of best fit ( alternatively called ' trendline ' ) 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 and is guaranteed to generate a correct solution in a finite time . No universal best - fit procedure is guaranteed to generate a correct solution for arbitrary relationships . A scatter plot is also very useful when we wish to see how two comparable data sets agre to show nonlinear relationships between variables . The ability to do this can be enhanced by adding a smooth line such as LOESS . Furthermore , if the data are represented by a mixture model of simple relationships , these relationships will be visually evident as superimposed patterns . </P>
<P> A scatter plot can suggest various kinds of correlations between variables with a certain confidence interval . For example , weight and height , weight would be on y axis and height would be on the x axis . Correlations may be positive ( rising ) , negative ( falling ) , or null ( uncorrelated ) . If the pattern of dots slopes from lower left to upper right , it indicates a positive correlation between the variables being studied . If the pattern of dots slopes from upper left to lower right , it indicates a negative correlation . A line of best fit ( alternatively called ' trendline ' ) 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 and is guaranteed to generate a correct solution in a finite time . No universal best - fit procedure is guaranteed to generate a correct solution for arbitrary relationships . A scatter plot is also very useful when we wish to see how two comparable data sets agre to show nonlinear relationships between variables . The ability to do this can be enhanced by adding a smooth line such as LOESS . Furthermore , if the data are represented by a mixture model of simple relationships , these relationships will be visually evident as superimposed patterns . </P>
what type of relationship is represented by the scatter plot
what type of relationship is represented by the scatter plot
positive ( rising ) negative ( falling ) null ( uncorrelated )
positive ( rising ) negative ( falling ) null ( uncorrelated )