b. square root of MSE
What is the standard error of estimate (SEE)?
The standard error of the estimate is a measure of the accuracy of predictions. Simply, it is used to check the accuracy of predictions made with the regression line.
Formula:
SEE = √(∑(y - ÿ)² / n)
Now, going through the options
a. square root of SSE
Formula of SSE:
SSE = ∑(y - ÿ)²
square root of SSE = √(∑(y - ÿ)²), which is not correct.
b. square root of MSE
Formula of MSE:
MSE = ∑(y - ÿ)² / n
square root of MSE = √(∑(y - ÿ)² / n), which is SSE, which is correct
c. standard deviation of t
Formula of standard deviation of t:
standard deviation of t = M-µ/ S, which is not correct
d. square root of SST
Formula of SST:
SST = ∑(y - ÿ)², which is not correct.
Hence the only correct answer is b. square root of MSE
Know more about "standard error of estimate" here: https://brainly.com/question/10002347
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