Asked by Chirag Berry on Jul 20, 2024
Verified
If the standard error of estimate sε = 20 and n = 10,then the sum of squares for error,SSE,is:
A) 400
B) 3,200
C) 4,000
D) 40,000
Standard Error Of Estimate
A measure of the accuracy of predictions made with a regression line, representing how spread out observed values are from the regression line.
Sum Of Squares For Error
The sum of squared differences between observed and predicted values in a regression model, measuring the discrepancy between the data and the model.
- Absorb the foundational ideas and numerical procedures relevant to the standard error of estimate in regression analytics.
Verified Answer
GM
Gardiny MarquisJul 20, 2024
Final Answer :
B
Explanation :
The sum of squares for error (SSE) can be calculated using the formula SSE = sε^2 * (n - 2), where sε is the standard error of estimate and n is the sample size. Plugging in the given values, sε = 20 and n = 10, we get SSE = 20^2 * (10 - 2) = 400 * 8 = 3,200.
Learning Objectives
- Absorb the foundational ideas and numerical procedures relevant to the standard error of estimate in regression analytics.