Quiz on Mean Squared Error (MSE)
Which of the following is the formula for MSE?
A)
B)
C)
D)
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Answer: B)
Explanation: The formula for MSE is the average of the squared differences between the observed actual outcomes and the predictions made by the model.
In the context of MSE, what does 
A) The predicted value
B) The observed value
C) The mean of observed values
D) The mean of predicted values
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Answer: B) The observed value
Explanation: In the formula for MSE,
What’s the biggest downside of using Mean Squared Error (MSE)?
A) It doesn’t care much about outliers ?
B) It’s tough to take derivatives of it ?
C) It might be unfair if the data isn’t normally distributed ?
D) It’s extra harsh on big mistakes ?
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Answer: D) It penalizes large errors more than smaller errors
Explanation: MSE squares the errors, so larger errors have a disproportionately higher impact, making it more sensitive to outliers.
Quiz on Mean Absolute Error (MAE)
Which of the following is the formula for MAE?
A)
B)
C)
D)
Show answer
Answer: A)
Explanation: The formula for MAE is the average of the absolute differences between the observed actual outcomes and the predictions made by the model.
Why might you pick Mean Absolute Error (MAE) over Mean Squared Error (MSE)?
A) It has a soft spot for outliers (more sensitive) ?
B) It’s kinder to outliers (less sensitive) ?
C) It’s simpler to understand ?
D) It’s tougher on big mistakes (penalizes large errors more) ?
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Answer: B) It is less sensitive to outliers
Explanation: MAE treats all errors equally by taking the absolute value, making it less sensitive to large outliers compared to MSE which squares the errors.
Quiz on Root Mean Squared Error (RMSE)
Which of the following is the formula for RMSE?
A)
B)
C)
D)
Show answer
Answer: C)
Explanation: The formula for RMSE is the square root of the MSE, providing a measure of error in the same units as the original data.
How does RMSE differ from MSE?
A) RMSE takes the square root of MSE
B) RMSE takes the absolute value of MSE
C) RMSE squares the MSE
D) RMSE averages the errors
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Answer: A) RMSE takes the square root of MSE
Explanation: RMSE is the square root of the Mean Squared Error, which adjusts the scale of the error metric to be in the same units as the original data.
Why might you choose RMSE over MSE?
A) It gives a straight-line scale of errors ?
B) It’s simpler to grasp ?
C) It’s even tougher on big mistakes than MSE ?
D) It shows error in the same units as the data ?
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Answer: D) It provides a measure of error in the same units as the data
Explanation: RMSE is preferred because it provides a measure of the error that is in the same units as the original data, making it easier to interpret.
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