On comparing the pairwise R - squared value between the three variables, we find that the line modeling the baking powder and the flour used can be expected to produce the most reliable predictions.
What is R - squared value ?
R-Squared value is a quantifiable analysis of how well the line of best fit (linear regression model) fits your data. A value closer to 1 (100%) is usually good.
The coefficient of determination - R - squared value is square of the correlation coefficient.
R - squared value of the relationship between baking powder and flour used = 0.953² = 0.908
R - squared value of the relationship between baking powder and butter used = 0.802² = 0.643
R - squared value of the relationship between flour and butter used = 0.693² = 0.48
Since, on comparing the R - squared values of the three relationships, we find that the R - squared value of the relationship between baking powder and flour used is largest. Thus, line of best fit between baking powder and flour is expected to produce the most reliable predictions.
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