![]() In both these cases, all of the original data points lie on a straight line. ![]() The slope of the line is negative (small values of X correspond to large values. The scatter about the line is quite small, so there is a strong linear relationship. Note in the plot above how a straight line comfortably fits through the data hence there is a linear relationship. And pause this video and think about what this one would be for you. If r 1, there is perfect negative correlation. Scatter Plot: Strong Linear (negative correlation) Relationship. Then, drag it to resize the Scatter plot. Firstly, select the plot and move the cursor to the edge. Finally, put a tick mark on Data Labels to show this. ![]() Secondly, from the Chart Elements > untick Gridlines to hide it. Why is Correlation Important How to Interpret Negative Correlation. Firstly, select the Correlation Scatter plot. Most software has a built-in correlation function. Negative, strong, Ill call it reasonably, Ill just say strong, but reasonably strong, linear, linear relationship between these two variables. Negative Correlation, Positive Correlation and Zero Correlation. Try this now on your calculator to see if you are getting your order of operations correct.įor our example, \(r = 0.8254\) is close to 1 therefore it looks like there is positive linear relationship between the number of hours studying for an exam and the grade on the exam.
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