What does a residual value of 1.3 mean when referring to the line of best fit of a data set?

The residual value of 1.3 mean when referring to the line of best fit of a data set is:

         The point lie 1.3 units above the line of best fit.

Residual value--

In statistics the residual value is the difference between the Measured value (i.e. the value on the scatter plot or the data point) and the  predicted value ( i.e. the value that lie on the line of best fit)

Hence, if the Residual value is positive then the point lie above the line of best fit and if the Residual value is negative then the data point lie below the line of best fit or trend line.

Hence, here the residual value is 1.3, this means that the data point lie 1.3 units above the line of best fit.

step-by-step explanation:

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“ a line segment that has the endpoints on the circle and passes through the midpoint is called the diameter. the diameter is twice the size of the radius. a line segment that has its endpoints on the circular border but does not pass through the midpoint is called a chord. a circle is the same as 360 small circle up the number 0 . i hope this .