The correlation coefficient, in this case, indicates a strong negative correlation between the variables in the data set. The value of -0.833 suggests that as one variable increases, the other variable tends to decrease.
Using a line of best fit, we can predict the value of the unknown variable based on its relationship with the known variable(s) in the data set. The line of best fit provides the most accurate estimate for the unknown value by minimizing the overall distance between the line and the data points.
With a correlation coefficient of -0.833, the line of best fit can be used to make predictions about the unknown value with reasonable accuracy. However, it is important to note that the line of best fit assumes a linear relationship between the variables, and any nonlinearities in the data may result in less accurate predictions. Additionally, it is essential to consider the range and variability of the data when making predictions with the line of best fit.
You use a line of best fit for a set of data to make a prediction about an unknown value. The correlation coefficient for your data set is -0.833.
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