Sue Lawlor is the management accountant at Tellie Manufacturing, an auto supplier that produces brake pads....

 

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Sue Lawlor is the management accountant at Tellie Manufacturing, an auto supplier that produces brake pads. Tellie's customers have high safety standards, and managers at Tellie believe they can gain a competitive advantage by reducing the number of defective parts they produce. Sue works with an external data science consulting company to develop a prediction model that identifies defective brake pads (y= 1) before they are shipped to Tellie's clients. After building the model on a training dataset, Sue tests its accuracy on the validation set below. Requirement 1. Calculate the likelihood value for each observation in the validation using the following equation: L = pxx (1-P)¹-Y (remember x¹ = x and x = 1). (Enter the likelihood values to two decimal places, X.XX.) Model probability (p) Actual outcome (y) Likelihood (L) 1 0.67 Observation number 2 5 3 4 0.01 0.33 0.20 0.01 1 0 0 6 0.33 0 7 0.01 0 Requirement 2. Calculate the overall likelihood value for the validation set. (Enter the overall likelihood to five decimal places, X.XXXXX.) Overall Likelihood Value = Requirement 3. As the management accountant, what should Sue do with this information? which indicates that it The overall likelihood value for this model is decision-making at the company. Sue should build a new model with a new testing sample and then, subsequently, a new validation sample. investigate different cutoff values and consider the payoff matrix to decide whether to use the model. Sue Lawlor is the management accountant at Tellie Manufacturing, an auto supplier that produces brake pads. have high safety standards, and managers at Tellie believe they can gain a competitive advantage by reducing defective parts they produce. Sue works with an external data science consulting company to develop a predict identifies defective brake pads (y= 1) before they are shipped to Tellie's clients. After building the model on a tr Sue tests its accuracy on the validation set below. Requirement 1. Calculate the likelihood value for each observation in the validation using the following equatic L = pyx (1-p)¹-y (remember x¹ = x and x = 1). (Enter the likelihood values to two decimal places, X.XX.) Model probability (p) Actual outcome (y) Likelihood (L) 1 2 0.67 0.01 0 Observation number 5 0.01 3 0.33 1 ***** 4 0.20 0 quite low 0 6 somewhat high 0.33 0 Requirement 2. Calculate the overall likelihood value for the validation set. (Enter the overall likelihood to five X.XXXXX.) Overall Likelihood Value = Requirement 3. As the management accountant, what should Sue do with this information? Jy which indicates that it The overall likelihood value for this model is decision-making at the company. Sue should 7 0.01 0 Sue Lawlor is the management accountant at Tellie Manufacturing, an auto supplier that produces brake pads. Tellie's custome have high safety standards, and managers at Tellie believe they can gain a competitive advantage by reducing the number of defective parts they produce. Sue works with an external data science consulting company to develop a prediction model that identifies defective brake pads (y = 1) before they are shipped to Tellie's clients. After building the model on a training dataset, Sue tests its accuracy on the validation set below. Requirement 1. Calculate the likelihood value for each observation in the validation using the following equation: L = px (1-p)¹-y (remember x¹ = x and x = 1). (Enter the likelihood values to two decimal places, X.XX.) Model probability (p) Actual outcome (y) Likelihood (L) 1 0.67 1 Observation number 5 0.01 2 3 4 0.01 0.33 0.20 0 1 0 0 6 0.33 0 7 0.01 Requirement 2. Calculate the overall likelihood value for the validation set. (Enter the overall likelihood to five decimal places, X.XXXXX.) Overall Likelihood Value = Requirement 3. As the management accountant, what should Sue do with this information? The overall likelihood value for this model is decision-making at the company. Sue should which indicates that it has potential to help improve will not improve Sue Lawlor is the management accountant at Tellie Manufacturing, an auto supplier that produces brake pads. Tellie's customers have high safety standards, and managers at Tellie believe they can gain a competitive advantage by reducing the number of defective parts they produce. Sue works with an external data science consulting company to develop a prediction model that identifies defective brake pads (y= 1) before they are shipped to Tellie's clients. After building the model on a training dataset, Sue tests its accuracy on the validation set below. Requirement 1. Calculate the likelihood value for each observation in the validation using the following equation: L = pxx (1-P)¹-Y (remember x¹ = x and x = 1). (Enter the likelihood values to two decimal places, X.XX.) Model probability (p) Actual outcome (y) Likelihood (L) 1 0.67 Observation number 2 5 3 4 0.01 0.33 0.20 0.01 1 0 0 6 0.33 0 7 0.01 0 Requirement 2. Calculate the overall likelihood value for the validation set. (Enter the overall likelihood to five decimal places, X.XXXXX.) Overall Likelihood Value = Requirement 3. As the management accountant, what should Sue do with this information? which indicates that it The overall likelihood value for this model is decision-making at the company. Sue should build a new model with a new testing sample and then, subsequently, a new validation sample. investigate different cutoff values and consider the payoff matrix to decide whether to use the model. Sue Lawlor is the management accountant at Tellie Manufacturing, an auto supplier that produces brake pads. have high safety standards, and managers at Tellie believe they can gain a competitive advantage by reducing defective parts they produce. Sue works with an external data science consulting company to develop a predict identifies defective brake pads (y= 1) before they are shipped to Tellie's clients. After building the model on a tr Sue tests its accuracy on the validation set below. Requirement 1. Calculate the likelihood value for each observation in the validation using the following equatic L = pyx (1-p)¹-y (remember x¹ = x and x = 1). (Enter the likelihood values to two decimal places, X.XX.) Model probability (p) Actual outcome (y) Likelihood (L) 1 2 0.67 0.01 0 Observation number 5 0.01 3 0.33 1 ***** 4 0.20 0 quite low 0 6 somewhat high 0.33 0 Requirement 2. Calculate the overall likelihood value for the validation set. (Enter the overall likelihood to five X.XXXXX.) Overall Likelihood Value = Requirement 3. As the management accountant, what should Sue do with this information? Jy which indicates that it The overall likelihood value for this model is decision-making at the company. Sue should 7 0.01 0 Sue Lawlor is the management accountant at Tellie Manufacturing, an auto supplier that produces brake pads. Tellie's custome have high safety standards, and managers at Tellie believe they can gain a competitive advantage by reducing the number of defective parts they produce. Sue works with an external data science consulting company to develop a prediction model that identifies defective brake pads (y = 1) before they are shipped to Tellie's clients. After building the model on a training dataset, Sue tests its accuracy on the validation set below. Requirement 1. Calculate the likelihood value for each observation in the validation using the following equation: L = px (1-p)¹-y (remember x¹ = x and x = 1). (Enter the likelihood values to two decimal places, X.XX.) Model probability (p) Actual outcome (y) Likelihood (L) 1 0.67 1 Observation number 5 0.01 2 3 4 0.01 0.33 0.20 0 1 0 0 6 0.33 0 7 0.01 Requirement 2. Calculate the overall likelihood value for the validation set. (Enter the overall likelihood to five decimal places, X.XXXXX.) Overall Likelihood Value = Requirement 3. As the management accountant, what should Sue do with this information? The overall likelihood value for this model is decision-making at the company. Sue should which indicates that it has potential to help improve will not improve

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