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University of South Florida *

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3000

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Statistics

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Feb 20, 2024

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Practice Questions (from class)

Questions 2 In a simple regression model having the form Y = f (X) + ε, what is meant by f (10)? (a) E (Y|X = 10) (b) Same as ̂ 𝑓𝑓 (10)? (c) 10th observed value of Y, y 10 (d) none of the above Suppose that you want to predict the values of a numerical response, Y, using a single numerical predicator, x. You expect that there is very nearly a linear relationship between E ( Y|x) and x, and the error term variance is relatively large. If the sample size of the training data is small, and the main focus is on obtaining accurate predictions of future values of Y for given new values of x, what should be done? (a) Use a simple inflexible regression method (b) Use a rather flexible regression method in order to better model the large deviations due to the large error term variance

Questions 3 What is the Bias and Variance tradeoff in data analytics? a) The tradeoff between model complexity and error b) The choice between categorical and numerical variables c) The decision to include outliers in the dataset How does increasing model complexity affect Bias and Variance? a) Increases both Bias and Variance b) Increases Bias, decreases Variance c) Decreases Bias, increases Variance d) Decreases both Bias and Variance Which statement is true regarding a high-bias model? a) It is likely to perform well on training data but poorly on new data b) It is likely to overfit the training data c) It is a balanced model with good generalization d) It has low sensitivity to noise in the training data

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Questions 4 In the context of Bias and Variance, what does "underfitting" refer to? a) Model fits the training data too closely b) Model fails to capture the underlying patterns in the data c) Model has low training error and high testing error d) Model has high flexibility and complexity What is the primary goal when trying to find the optimal Bias-Variance tradeoff? a) Minimize training error b) Minimize testing error c) Maximize model complexity d) Maximize the number of features Which scenario is indicative of a tradeoff between Bias and Variance? a) Low Bias, Low Variance b) High Bias, High Variance c) Low Bias, High Variance d) High Bias, Low Variance

Question 5 • What will the ROC curve look like? • Match the correct representation for each figure from the left column to one figure on the right column 1 2 a b c Sensitivity (TPR) 1-Specificity (FPR)

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