Asked by Amber Porter on Jun 27, 2024
Verified
In a regression analysis, the standard error of the estimate is determined to be 4.In this situation, the MSE
A) is 2.
B) is 16.
C) depends on the sample size.
D) requires a known SSE.
Standard Error
The standard deviation of the sampling distribution of a statistic, typically the mean, indicating the variability of sampling estimates.
SSE
Sum of Squared Errors; a measure used in statistics to describe the total deviation of data points from a fitted value, reflecting the discrepancy between observed and predicted values.
- Understand the method of computing and analyzing the mean square error (MSE), as well as its significance in the context of regression analysis.
Verified Answer
ES
Erick SepulvedaJun 28, 2024
Final Answer :
B
Explanation :
The standard error of the estimate (also known as the root mean squared error) is equal to the square root of the mean squared error (MSE). Therefore, if the standard error of the estimate is 4, the MSE is equal to 4 squared, which is 16. The MSE does not depend on the sample size and can be calculated directly from the standard error of the estimate without requiring knowledge of the SSE.
Learning Objectives
- Understand the method of computing and analyzing the mean square error (MSE), as well as its significance in the context of regression analysis.
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