ms2002_2026T2_Q1_NA.pdf

**(The following scenario is purely Imaginary)** Milo’s Evaluation (ME) is a loan default prediction company that uses manual workforce to suggest possible defaulters. Dr. Milo, the Chief Data Officer of ME, has decided to replace the manual workforce with a cutting-edge Logistic Regression Model that takes “Age” and “Income” as parameters to predict defaulters. The model is configured such that a “NOT DEFAULTER” is categorised as the positive class. The final model had the parameters as specified in Table-1 below. To test the model, the data in Table-2 is used as test data. Given this information, answer the given subquestions. [[IMAGE:a4d71fbe720d335c_2_2]] [[IMAGE:a4d71fbe720d335c_3_3]] Note: For all computations (both final and those done in the middle), **round your answer to two** **decimal places**. Do not use single decimal values for any computation or comparisons.

At a threshold of 0.6, how many “True Positives” is the model predicting?

**(The following scenario is purely Imaginary)** Milo’s Evaluation (ME) is a loan default prediction company that uses manual workforce to suggest possible defaulters. Dr. Milo, the Chief Data Officer of ME, has decided to replace the manual workforce with a cutting-edge Logistic Regression Model that takes “Age” and “Income” as parameters to predict defaulters. The model is configured such that a “NOT DEFAULTER” is categorised as the positive class. The final model had the parameters as specified in Table-1 below. To test the model, the data in Table-2 is used as test data. Given this information, answer the given subquestions. [[IMAGE:a4d71fbe720d335c_2_2]] [[IMAGE:a4d71fbe720d335c_3_3]] Note: For all computations (both final and those done in the middle), **round your answer to two** **decimal places**. Do not use single decimal values for any computation or comparisons.

At a threshold of 0.6, how many “True Negatives” is the model predicting?

**(The following scenario is purely Imaginary)** Milo’s Evaluation (ME) is a loan default prediction company that uses manual workforce to suggest possible defaulters. Dr. Milo, the Chief Data Officer of ME, has decided to replace the manual workforce with a cutting-edge Logistic Regression Model that takes “Age” and “Income” as parameters to predict defaulters. The model is configured such that a “NOT DEFAULTER” is categorised as the positive class. The final model had the parameters as specified in Table-1 below. To test the model, the data in Table-2 is used as test data. Given this information, answer the given subquestions. [[IMAGE:a4d71fbe720d335c_2_2]] [[IMAGE:a4d71fbe720d335c_3_3]] Note: For all computations (both final and those done in the middle), **round your answer to two** **decimal places**. Do not use single decimal values for any computation or comparisons.

At a threshold of 0.6, how many “False Positives” is the model predicting?

**(The following scenario is purely Imaginary)** Milo’s Evaluation (ME) is a loan default prediction company that uses manual workforce to suggest possible defaulters. Dr. Milo, the Chief Data Officer of ME, has decided to replace the manual workforce with a cutting-edge Logistic Regression Model that takes “Age” and “Income” as parameters to predict defaulters. The model is configured such that a “NOT DEFAULTER” is categorised as the positive class. The final model had the parameters as specified in Table-1 below. To test the model, the data in Table-2 is used as test data. Given this information, answer the given subquestions. [[IMAGE:a4d71fbe720d335c_2_2]] [[IMAGE:a4d71fbe720d335c_3_3]] Note: For all computations (both final and those done in the middle), **round your answer to two** **decimal places**. Do not use single decimal values for any computation or comparisons.

At a threshold of 0.6, how many “False Negatives” is the model predicting?

**(The following scenario is purely Imaginary)** Milo’s Evaluation (ME) is a loan default prediction company that uses manual workforce to suggest possible defaulters. Dr. Milo, the Chief Data Officer of ME, has decided to replace the manual workforce with a cutting-edge Logistic Regression Model that takes “Age” and “Income” as parameters to predict defaulters. The model is configured such that a “NOT DEFAULTER” is categorised as the positive class. The final model had the parameters as specified in Table-1 below. To test the model, the data in Table-2 is used as test data. Given this information, answer the given subquestions. [[IMAGE:a4d71fbe720d335c_2_2]] [[IMAGE:a4d71fbe720d335c_3_3]] Note: For all computations (both final and those done in the middle), **round your answer to two** **decimal places**. Do not use single decimal values for any computation or comparisons.

At a threshold of 0.6, what is the ACCURACY of the model? (Note: **Enter the answer in “%”** rounded to two decimal places without the “%” symbol. For example, if the answer is “1.234%”, then enter it as “1.23”)

**(The following scenario is purely Imaginary)** Milo’s Evaluation (ME) is a loan default prediction company that uses manual workforce to suggest possible defaulters. Dr. Milo, the Chief Data Officer of ME, has decided to replace the manual workforce with a cutting-edge Logistic Regression Model that takes “Age” and “Income” as parameters to predict defaulters. The model is configured such that a “NOT DEFAULTER” is categorised as the positive class. The final model had the parameters as specified in Table-1 below. To test the model, the data in Table-2 is used as test data. Given this information, answer the given subquestions. [[IMAGE:a4d71fbe720d335c_2_2]] [[IMAGE:a4d71fbe720d335c_3_3]] Note: For all computations (both final and those done in the middle), **round your answer to two** **decimal places**. Do not use single decimal values for any computation or comparisons.

At a threshold of 0.6, what is the PRECISION of the model for predicting the Negative Class? (Note: **Enter the answer in “%”** rounded to two decimal places without the “%” symbol. For example, if the answer is “1.234%”, then enter it as “1.23”)

**(The following scenario is purely Imaginary)** Milo’s Evaluation (ME) is a loan default prediction company that uses manual workforce to suggest possible defaulters. Dr. Milo, the Chief Data Officer of ME, has decided to replace the manual workforce with a cutting-edge Logistic Regression Model that takes “Age” and “Income” as parameters to predict defaulters. The model is configured such that a “NOT DEFAULTER” is categorised as the positive class. The final model had the parameters as specified in Table-1 below. To test the model, the data in Table-2 is used as test data. Given this information, answer the given subquestions. [[IMAGE:a4d71fbe720d335c_2_2]] [[IMAGE:a4d71fbe720d335c_3_3]] Note: For all computations (both final and those done in the middle), **round your answer to two** **decimal places**. Do not use single decimal values for any computation or comparisons.

At a threshold of 0.6, what is the SPECIFICITY of the model? (Note: **Enter the answer in “%”** rounded to two decimal places without the “%” symbol. For example, if the answer is “1.234%”, then enter it as “1.23”)

**(The following scenario is purely Imaginary)** Milo’s Evaluation (ME) is a loan default prediction company that uses manual workforce to suggest possible defaulters. Dr. Milo, the Chief Data Officer of ME, has decided to replace the manual workforce with a cutting-edge Logistic Regression Model that takes “Age” and “Income” as parameters to predict defaulters. The model is configured such that a “NOT DEFAULTER” is categorised as the positive class. The final model had the parameters as specified in Table-1 below. To test the model, the data in Table-2 is used as test data. Given this information, answer the given subquestions. [[IMAGE:a4d71fbe720d335c_2_2]] [[IMAGE:a4d71fbe720d335c_3_3]] Note: For all computations (both final and those done in the middle), **round your answer to two** **decimal places**. Do not use single decimal values for any computation or comparisons.

At a threshold of 0.6, what is the SENSITIVITY of the model? (Note: **Enter the answer in “%”** rounded to two decimal places without the “%” symbol. For example, if the answer is “1.234%”, then enter it as “1.23”)

**(The following scenario is purely Imaginary)** A demand response curve has a constant elasticity of +0.4. If the price of the product is 100 and the corresponding demand is 200, then answer the given subquestions.

What is the value for the constant term of the demand response curve? (Note: Enter the answer rounded to two decimal places. For example, if the answer is “1.234”, then enter it as “1.23”)

**(The following scenario is purely Imaginary)** A demand response curve has a constant elasticity of +0.4. If the price of the product is 100 and the corresponding demand is 200, then answer the given subquestions.

What should be the price to achieve a demand of 300? (Note: Enter the answer rounded to two decimal places. For example, if the answer is “1.234”, then enter it as “1.23”)

**(The following scenario is purely Imaginary)** “Fake Money (FM)” is an investment consulting firm. Dr. Milo has approached FM with Rs. 1,00,000 for guidance on investment opportunities. Dr. Milo wants to invest the entire Rs. 1,00,000. FM’s top financial analyst recommends that all new investments be made in oil industry, steel industry or government bonds. Specifically, the analyst identified five investment opportunities and projected their annual rates of returns (which are specified in Table-3). Dr. Milo, is a guy who likes to distribute his investments. Hence, he has specified the following requirements to the analyst 1. Neither industry (oil or steel) should receive more than Rs. 50,000 2. Government bonds should be exactly 25% of the total steel industry investments 3. Government bonds can at most be 30% of the total oil industry investments 4. The investments in Bongu Oil, the high-return but high-risk investment, cannot be more than 60% of total oil industry investment [[IMAGE:a4d71fbe720d335c_7_4]] Given this information, answer the given subquestions

How many (count of) decision variable(s) is/are present in the standard (canonical) form of the primal?

**(The following scenario is purely Imaginary)** “Fake Money (FM)” is an investment consulting firm. Dr. Milo has approached FM with Rs. 1,00,000 for guidance on investment opportunities. Dr. Milo wants to invest the entire Rs. 1,00,000. FM’s top financial analyst recommends that all new investments be made in oil industry, steel industry or government bonds. Specifically, the analyst identified five investment opportunities and projected their annual rates of returns (which are specified in Table-3). Dr. Milo, is a guy who likes to distribute his investments. Hence, he has specified the following requirements to the analyst 1. Neither industry (oil or steel) should receive more than Rs. 50,000 2. Government bonds should be exactly 25% of the total steel industry investments 3. Government bonds can at most be 30% of the total oil industry investments 4. The investments in Bongu Oil, the high-return but high-risk investment, cannot be more than 60% of total oil industry investment [[IMAGE:a4d71fbe720d335c_7_4]] Given this information, answer the given subquestions

How many constraints (count of constraints, excluding the non-negativity constraints) is present in the standard (canonical) form of the primal?

**(The following scenario is purely Imaginary)** “Fake Money (FM)” is an investment consulting firm. Dr. Milo has approached FM with Rs. 1,00,000 for guidance on investment opportunities. Dr. Milo wants to invest the entire Rs. 1,00,000. FM’s top financial analyst recommends that all new investments be made in oil industry, steel industry or government bonds. Specifically, the analyst identified five investment opportunities and projected their annual rates of returns (which are specified in Table-3). Dr. Milo, is a guy who likes to distribute his investments. Hence, he has specified the following requirements to the analyst 1. Neither industry (oil or steel) should receive more than Rs. 50,000 2. Government bonds should be exactly 25% of the total steel industry investments 3. Government bonds can at most be 30% of the total oil industry investments 4. The investments in Bongu Oil, the high-return but high-risk investment, cannot be more than 60% of total oil industry investment [[IMAGE:a4d71fbe720d335c_7_4]] Given this information, answer the given subquestions

How many (count of) decision variables are present in the dual (which is based on the standard (canonical) form of the primal)?

**(The following scenario is purely Imaginary)** “Fake Money (FM)” is an investment consulting firm. Dr. Milo has approached FM with Rs. 1,00,000 for guidance on investment opportunities. Dr. Milo wants to invest the entire Rs. 1,00,000. FM’s top financial analyst recommends that all new investments be made in oil industry, steel industry or government bonds. Specifically, the analyst identified five investment opportunities and projected their annual rates of returns (which are specified in Table-3). Dr. Milo, is a guy who likes to distribute his investments. Hence, he has specified the following requirements to the analyst 1. Neither industry (oil or steel) should receive more than Rs. 50,000 2. Government bonds should be exactly 25% of the total steel industry investments 3. Government bonds can at most be 30% of the total oil industry investments 4. The investments in Bongu Oil, the high-return but high-risk investment, cannot be more than 60% of total oil industry investment [[IMAGE:a4d71fbe720d335c_7_4]] Given this information, answer the given subquestions

If FM has suggested the below distribution of investments, then how much money (total money) is projected to be in hand at the end of the first year? (Note: **Enter the answer in “Rs.”** rounded to two decimal places without the “Rs.” symbol. For example, if the answer is “Rs. 1.234”, then enter it as “1.23”) [[IMAGE:a4d71fbe720d335c_9_5]]

**(The following scenario is purely Imaginary)** “Fake Money (FM)” is an investment consulting firm. Dr. Milo has approached FM with Rs. 1,00,000 for guidance on investment opportunities. Dr. Milo wants to invest the entire Rs. 1,00,000. FM’s top financial analyst recommends that all new investments be made in oil industry, steel industry or government bonds. Specifically, the analyst identified five investment opportunities and projected their annual rates of returns (which are specified in Table-3). Dr. Milo, is a guy who likes to distribute his investments. Hence, he has specified the following requirements to the analyst 1. Neither industry (oil or steel) should receive more than Rs. 50,000 2. Government bonds should be exactly 25% of the total steel industry investments 3. Government bonds can at most be 30% of the total oil industry investments 4. The investments in Bongu Oil, the high-return but high-risk investment, cannot be more than 60% of total oil industry investment [[IMAGE:a4d71fbe720d335c_7_4]] Given this information, answer the given subquestions

If FM has suggested the below distribution of investments, then how many decision variables in the dual will have a **“zero”** value? [[IMAGE:a4d71fbe720d335c_9_6]]

**(The following scenario is purely Imaginary)** “Fake Money (FM)” is an investment consulting firm. Dr. Milo has approached FM with Rs. 1,00,000 for guidance on investment opportunities. Dr. Milo wants to invest the entire Rs. 1,00,000. FM’s top financial analyst recommends that all new investments be made in oil industry, steel industry or government bonds. Specifically, the analyst identified five investment opportunities and projected their annual rates of returns (which are specified in Table-3). Dr. Milo, is a guy who likes to distribute his investments. Hence, he has specified the following requirements to the analyst 1. Neither industry (oil or steel) should receive more than Rs. 50,000 2. Government bonds should be exactly 25% of the total steel industry investments 3. Government bonds can at most be 30% of the total oil industry investments 4. The investments in Bongu Oil, the high-return but high-risk investment, cannot be more than 60% of total oil industry investment [[IMAGE:a4d71fbe720d335c_7_4]] Given this information, answer the given subquestions

If FM has suggested the below distribution of investments, then what is the objective function value for the primal in the standard (canonical) form? [[IMAGE:a4d71fbe720d335c_10_7]]

**(The following scenario is purely Imaginary)** Milo’s Bakery is famous for three products “BA Biscuits (BAB)”, “TA Controversy Cake (TACC)” and “Hot Argument Drink (HAD)”. Dr.Milo, the owner of the shop, is an aspiring data analyst. He has collected 5 days of data. On each day, he captures the number of each product made and total kilogram of cooking gas consumed. Using all the collected data, Dr.Milo has built a linear regression model in excel, and the partial regression output is provided in Figure-2. Using this information, answer the given subquestions [[IMAGE:a4d71fbe720d335c_11_8]] Note: For all computations (both final and those done in the middle), **round your answer to two** **decimal places**. Do not use single decimal values for any computation or comparisons.

What is the sample size for building the model in Figure-2?

**(The following scenario is purely Imaginary)** Milo’s Bakery is famous for three products “BA Biscuits (BAB)”, “TA Controversy Cake (TACC)” and “Hot Argument Drink (HAD)”. Dr.Milo, the owner of the shop, is an aspiring data analyst. He has collected 5 days of data. On each day, he captures the number of each product made and total kilogram of cooking gas consumed. Using all the collected data, Dr.Milo has built a linear regression model in excel, and the partial regression output is provided in Figure-2. Using this information, answer the given subquestions [[IMAGE:a4d71fbe720d335c_11_8]] Note: For all computations (both final and those done in the middle), **round your answer to two** **decimal places**. Do not use single decimal values for any computation or comparisons.

What is the value of Q1?

**(The following scenario is purely Imaginary)** Milo’s Bakery is famous for three products “BA Biscuits (BAB)”, “TA Controversy Cake (TACC)” and “Hot Argument Drink (HAD)”. Dr.Milo, the owner of the shop, is an aspiring data analyst. He has collected 5 days of data. On each day, he captures the number of each product made and total kilogram of cooking gas consumed. Using all the collected data, Dr.Milo has built a linear regression model in excel, and the partial regression output is provided in Figure-2. Using this information, answer the given subquestions [[IMAGE:a4d71fbe720d335c_11_8]] Note: For all computations (both final and those done in the middle), **round your answer to two** **decimal places**. Do not use single decimal values for any computation or comparisons.

What is the value of Q2? (Note: Enter your answer rounded to two decimal places. For example, if your answer is “1.235” then enter it as “1.24”)

**(The following scenario is purely Imaginary)** Milo’s Bakery is famous for three products “BA Biscuits (BAB)”, “TA Controversy Cake (TACC)” and “Hot Argument Drink (HAD)”. Dr.Milo, the owner of the shop, is an aspiring data analyst. He has collected 5 days of data. On each day, he captures the number of each product made and total kilogram of cooking gas consumed. Using all the collected data, Dr.Milo has built a linear regression model in excel, and the partial regression output is provided in Figure-2. Using this information, answer the given subquestions [[IMAGE:a4d71fbe720d335c_11_8]] Note: For all computations (both final and those done in the middle), **round your answer to two** **decimal places**. Do not use single decimal values for any computation or comparisons.

What is the value of Q3? (Note: Enter your answer rounded to two decimal places. For example, if your answer is “1.235” then enter it as “1.24”)

**(The following scenario is purely Imaginary)** Milo’s Bakery is famous for three products “BA Biscuits (BAB)”, “TA Controversy Cake (TACC)” and “Hot Argument Drink (HAD)”. Dr.Milo, the owner of the shop, is an aspiring data analyst. He has collected 5 days of data. On each day, he captures the number of each product made and total kilogram of cooking gas consumed. Using all the collected data, Dr.Milo has built a linear regression model in excel, and the partial regression output is provided in Figure-2. Using this information, answer the given subquestions [[IMAGE:a4d71fbe720d335c_11_8]] Note: For all computations (both final and those done in the middle), **round your answer to two** **decimal places**. Do not use single decimal values for any computation or comparisons.

What is the value of Q4? (Note: Enter your answer rounded to two decimal places. For example, if your answer is “1.235” then enter it as “1.24”)

**(The following scenario is purely Imaginary)** Milo’s Bakery is famous for three products “BA Biscuits (BAB)”, “TA Controversy Cake (TACC)” and “Hot Argument Drink (HAD)”. Dr.Milo, the owner of the shop, is an aspiring data analyst. He has collected 5 days of data. On each day, he captures the number of each product made and total kilogram of cooking gas consumed. Using all the collected data, Dr.Milo has built a linear regression model in excel, and the partial regression output is provided in Figure-2. Using this information, answer the given subquestions [[IMAGE:a4d71fbe720d335c_11_8]] Note: For all computations (both final and those done in the middle), **round your answer to two** **decimal places**. Do not use single decimal values for any computation or comparisons.

What is the value of Q5? (Note: Enter your answer rounded to two decimal places. For example, if your answer is “1.235” then enter it as “1.24”)