Question

After fitting a line to some data and doing the proper error analysis, you find the slope of the best-fit line to be m = 6.4 ± 0.3 and the y-intercept to be b = 0.6 ± 0.1. Explicitly, your data is well described by a line according to the equation: y = m*x + b Now you want to use your best-fit line to predict what the y-value should be for a x-value data point that wasn't in your original data set. If this x data point is 0.36 ± 0.02, what is the absolute uncertainty, dy, in the y-value that corresponds to this x-data point (again using only one significant digit for your answer)?

          After fitting a line to some data and doing the proper error analysis, you find the slope of the best-fit line to be m = 6.4 ± 0.3 and the y-intercept to be b = 0.6 ± 0.1. Explicitly, your data is well described by a line according to the equation:

y = m*x + b

Now you want to use your best-fit line to predict what the y-value should be for a x-value data point that wasn't in your original data set. If this x data point is 0.36 ± 0.02, what is the absolute uncertainty, dy, in the y-value that corresponds to this x-data point (again using only one significant digit for your answer)?

After fitting a line to some data and doing the proper error analysis, you find the slope of the best-fit line to be m = 6.4 ± 0.3 and the y-intercept to be b = 0.6 ± 0.1. Explicitly, your data is well described by a line according to the equation:

y = m*x + b

Now you want to use your best-fit line to predict what the y-value should be for a x-value data point that wasn't in your original data set. If this x data point is 0.36 ± 0.02, what is the absolute uncertainty, dy, in the y-value that corresponds to this x-data point (again using only one significant digit for your answer)?

Added by Patrick O.

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