Question 1
The distribution is right skewed
The distribution is symmetric
The distribution is left skewed
Cannot say without the skewness value
The IIT Madras BS Business Analytics (Business Analytics) End Term paper sat on 24 Dec 2023, in the September 2023 term, set FDD1: 34 questions for 45 marks in 180 minutes. Every question is below with its answer. Take it as a timed mock test to be marked, or read it through first.
The distribution is right skewed
The distribution is symmetric
The distribution is left skewed
Cannot say without the skewness value
Correct answer
The distribution is right skewed
There are 4 business units. There are two outputs and one input under consideration. You are solving the optimization problem for business unit 3 and find that the efficiency is 0.8. You find that the dual variables corresponding to the constraints of business units 3 and 5 are non-zero and the dual variables corresponding to the constraints of other units are zero. The dual variables corresponding to the constraints of business units 3 and 5 are 0.35 and 0.45 respectively. You are given the following table where sales and number of leads are the two outputs. What is the Market Share in HCU 4?
Hint: Round off answers to 4 decimal places in every step of your calculation
| Total Profit (1000 $) | Market Share (%) | |
|---|---|---|
| DMU 3 | 15,000 | 55% |
| DMU 5 | 18,000 | 60% |
67.8125
47.8125
65.8128
57.8125
Correct answer
57.8125
In the below diagram, the customer wants to decide between the products O1 & O2, and x denotes the coordinates of the ideal product. Which of the following are true?
Customers will prefer O2 when d1<d2
Both Customers will prefer O2 when d1<d2 and Customers will prefer O1 when d2>d1
Customers will prefer O1 when d2>d1
None of these
Correct answer
Customers will prefer O1 when d2>d1
Data Envelopment Analysis (DEA) is a method for:
Measuring a firm's quality performance by comparing it with other companies that are recognized as "best in class."
Determining the feasibility of technological innovations in service operations.
Comparing the efficiency of multiple service units that provide similar services.
Analyzing the gap between the service customer's expectations and perceptions.
Correct answer
Comparing the efficiency of multiple service units that provide similar services.
Correct answer
If the attribute values in the conjoint analysis is a continuous variable and the data is collected in a pairwise order, then what approach can be used:
Regression or Statistical approach
Optimization approach
Both Regression or Statistical approach and Optimization approach
None of these
Correct answer
Optimization approach
The part worth can be defined as:
Level utilities
The utility for that level of attribute
Utility for separate parts of the products
Both Level utilities and The utility for that level of attribute
All of these
Correct answer
All of these
What is productive efficiency?
Consists of all combinations of outputs such that the production of one product cannot be increased without sacrificing the output of the other (without any change in technology)
It is an aspect of economic efficiency focussing on maximizing the output under given constraints.
Productive efficiency does not worry about optimal allocation, or choice of products
Both Consists of all combinations of outputs such that the production of one product cannot be increased without sacrificing the output of the other (without any change in technology) and It is an aspect of economic efficiency focussing on maximizing the output under given constraints.
Both It is an aspect of economic efficiency focussing on maximizing the output under given constraints and Productive efficiency does not worry about optimal allocation, or choice of products
Correct answers
It is an aspect of economic efficiency focussing on maximizing the output under given constraints.
Productive efficiency does not worry about optimal allocation, or choice of products
There are 7 business units and you are using the DEA to compare them. You solve the LP for business unit 5. You find from the constraint expression that business unit 4 has obtained an efficiency of 0.9 and business unit 2 has obtained an efficiency of 0.6 with the optimal weights of business unit 5. Which of the following statements is correct?
Business unit 5 may be inefficient
Business unit 4 will be inefficient
Business unit 5 may be efficient
Business unit 2 will be inefficient
Correct answers
Business unit 4 will be inefficient
Business unit 2 will be inefficient
An ice cream seller has collected data on the number of ice-creams sold by him in two streets “A” and “B” over the past 15 days. This data is provided in Table-1. The number of ice creams sold in street “A” is expected to follow a uniform distribution. Based on the sample, you decide to perform a statistical test with the following bins [75 to 100), [100 to 125), [125 to 150), [150 to 175].
Given this information, answer the given subquestions.
| Number of Ice-Creams Sold in Street-A | Number of Ice-Creams Sold in Street-B | |
|---|---|---|
| Day-1 | 120 | 85 |
| Day-2 | 130 | 75 |
| Day-3 | 75 | 120 |
| Day-4 | 160 | 80 |
| Day-5 | 130 | 160 |
| Day-6 | 120 | 75 |
| Day-7 | 120 | 78 |
| Day-8 | 75 | 130 |
| Day-9 | 75 | 143 |
| Day-10 | 75 | 154 |
| Day-11 | 75 | 122 |
| Day-12 | 160 | 90 |
| Day-13 | 160 | 85 |
| Day-14 | 130 | 79 |
| Day-15 | 160 | 97 |
Table-1
What is the expected number of ice-creams that will be sold in any given bin? (Note: Enter the answer rounded to two decimal places. For example, if the answer is “1.234”, then enter it as “1.23”)
Correct answer: 3.5
An ice cream seller has collected data on the number of ice-creams sold by him in two streets “A” and “B” over the past 15 days. This data is provided in Table-1. The number of ice creams sold in street “A” is expected to follow a uniform distribution. Based on the sample, you decide to perform a statistical test with the following bins [75 to 100), [100 to 125), [125 to 150), [150 to 175].
Given this information, answer the given subquestions.
| Number of Ice-Creams Sold in Street-A | Number of Ice-Creams Sold in Street-B | |
|---|---|---|
| Day-1 | 120 | 85 |
| Day-2 | 130 | 75 |
| Day-3 | 75 | 120 |
| Day-4 | 160 | 80 |
| Day-5 | 130 | 160 |
| Day-6 | 120 | 75 |
| Day-7 | 120 | 78 |
| Day-8 | 75 | 130 |
| Day-9 | 75 | 143 |
| Day-10 | 75 | 154 |
| Day-11 | 75 | 122 |
| Day-12 | 160 | 90 |
| Day-13 | 160 | 85 |
| Day-14 | 130 | 79 |
| Day-15 | 160 | 97 |
Table-1
What is the “Degrees of Freedom” for the statistical test that will be performed? (Note: Enter the answer rounded to two decimal places. For example, if the answer is “1.234”, then enter it as “1.23”)
Correct answer: 1
An ice cream seller has collected data on the number of ice-creams sold by him in two streets “A” and “B” over the past 15 days. This data is provided in Table-1. The number of ice creams sold in street “A” is expected to follow a uniform distribution. Based on the sample, you decide to perform a statistical test with the following bins [75 to 100), [100 to 125), [125 to 150), [150 to 175].
Given this information, answer the given subquestions.
| Number of Ice-Creams Sold in Street-A | Number of Ice-Creams Sold in Street-B | |
|---|---|---|
| Day-1 | 120 | 85 |
| Day-2 | 130 | 75 |
| Day-3 | 75 | 120 |
| Day-4 | 160 | 80 |
| Day-5 | 130 | 160 |
| Day-6 | 120 | 75 |
| Day-7 | 120 | 78 |
| Day-8 | 75 | 130 |
| Day-9 | 75 | 143 |
| Day-10 | 75 | 154 |
| Day-11 | 75 | 122 |
| Day-12 | 160 | 90 |
| Day-13 | 160 | 85 |
| Day-14 | 130 | 79 |
| Day-15 | 160 | 97 |
Table-1
What is the value of the computed test statistic? (Note: Enter the answer rounded to two decimal places. For example, if the answer is “1.234”, then enter it as “1.23”)
Correct answer: 2.5 (accepted within ±0.2)
An ice cream seller has collected data on the number of ice-creams sold by him in two streets “A” and “B” over the past 15 days. This data is provided in Table-1. The number of ice creams sold in street “A” is expected to follow a uniform distribution. Based on the sample, you decide to perform a statistical test with the following bins [75 to 100), [100 to 125), [125 to 150), [150 to 175].
Given this information, answer the given subquestions.
| Number of Ice-Creams Sold in Street-A | Number of Ice-Creams Sold in Street-B | |
|---|---|---|
| Day-1 | 120 | 85 |
| Day-2 | 130 | 75 |
| Day-3 | 75 | 120 |
| Day-4 | 160 | 80 |
| Day-5 | 130 | 160 |
| Day-6 | 120 | 75 |
| Day-7 | 120 | 78 |
| Day-8 | 75 | 130 |
| Day-9 | 75 | 143 |
| Day-10 | 75 | 154 |
| Day-11 | 75 | 122 |
| Day-12 | 160 | 90 |
| Day-13 | 160 | 85 |
| Day-14 | 130 | 79 |
| Day-15 | 160 | 97 |
Table-1
If the tabulated value of the test statistic is 8.92, then which of the following statements are correct?
Reject the Null and conclude that the number ice-cream sold in Street-A follows a uniform distribution
Do Not Reject the Null and conclude that the number ice-cream sold in Street- A follows a uniform distribution
Reject the Null and conclude that the number ice-cream sold in Street-A does not follows a uniform distribution
Do Not Reject the Null and conclude that the number ice-cream sold in Street- A does not follows a uniform distribution
Correct answer
Do Not Reject the Null and conclude that the number ice-cream sold in Street- A follows a uniform distribution
An ice cream seller has collected data on the number of ice-creams sold by him in two streets “A” and “B” over the past 15 days. This data is provided in Table-1. The number of ice creams sold in street “A” is expected to follow a uniform distribution. Based on the sample, you decide to perform a statistical test with the following bins [75 to 100), [100 to 125), [125 to 150), [150 to 175].
Given this information, answer the given subquestions.
| Number of Ice-Creams Sold in Street-A | Number of Ice-Creams Sold in Street-B | |
|---|---|---|
| Day-1 | 120 | 85 |
| Day-2 | 130 | 75 |
| Day-3 | 75 | 120 |
| Day-4 | 160 | 80 |
| Day-5 | 130 | 160 |
| Day-6 | 120 | 75 |
| Day-7 | 120 | 78 |
| Day-8 | 75 | 130 |
| Day-9 | 75 | 143 |
| Day-10 | 75 | 154 |
| Day-11 | 75 | 122 |
| Day-12 | 160 | 90 |
| Day-13 | 160 | 85 |
| Day-14 | 130 | 79 |
| Day-15 | 160 | 97 |
Table-1
How many degrees of freedom is present for the test used to determine if the sales in “Street-A” and “Street-B” are not-dependent on each other across days? (Note: Enter the answer rounded to two decimal places. For example, if the answer is “1.234”, then enter it as “1.23”)
Correct answer: 14
An ice cream seller has collected data on the number of ice-creams sold by him in two streets “A” and “B” over the past 15 days. This data is provided in Table-1. The number of ice creams sold in street “A” is expected to follow a uniform distribution. Based on the sample, you decide to perform a statistical test with the following bins [75 to 100), [100 to 125), [125 to 150), [150 to 175].
Given this information, answer the given subquestions.
| Number of Ice-Creams Sold in Street-A | Number of Ice-Creams Sold in Street-B | |
|---|---|---|
| Day-1 | 120 | 85 |
| Day-2 | 130 | 75 |
| Day-3 | 75 | 120 |
| Day-4 | 160 | 80 |
| Day-5 | 130 | 160 |
| Day-6 | 120 | 75 |
| Day-7 | 120 | 78 |
| Day-8 | 75 | 130 |
| Day-9 | 75 | 143 |
| Day-10 | 75 | 154 |
| Day-11 | 75 | 122 |
| Day-12 | 160 | 90 |
| Day-13 | 160 | 85 |
| Day-14 | 130 | 79 |
| Day-15 | 160 | 97 |
Table-1
If the aim is to find if the sales in “Street-A” and “Street-B” are independent on each other across days, then what is the expected sales on “Day-10” for “Street-A”? (Note: Enter the answer rounded to two decimal places. For example, if the answer is “1.234”, then enter it as “1.23”)
Correct answer: 121.5 (accepted within ±0.5)
An ice cream seller has collected data on the number of ice-creams sold by him in two streets “A” and “B” over the past 15 days. This data is provided in Table-1. The number of ice creams sold in street “A” is expected to follow a uniform distribution. Based on the sample, you decide to perform a statistical test with the following bins [75 to 100), [100 to 125), [125 to 150), [150 to 175].
Given this information, answer the given subquestions.
| Number of Ice-Creams Sold in Street-A | Number of Ice-Creams Sold in Street-B | |
|---|---|---|
| Day-1 | 120 | 85 |
| Day-2 | 130 | 75 |
| Day-3 | 75 | 120 |
| Day-4 | 160 | 80 |
| Day-5 | 130 | 160 |
| Day-6 | 120 | 75 |
| Day-7 | 120 | 78 |
| Day-8 | 75 | 130 |
| Day-9 | 75 | 143 |
| Day-10 | 75 | 154 |
| Day-11 | 75 | 122 |
| Day-12 | 160 | 90 |
| Day-13 | 160 | 85 |
| Day-14 | 130 | 79 |
| Day-15 | 160 | 97 |
Table-1
If the aim is to find if the sales in “Street-A” and “Street-B” are independent on each other across days, then what is the expected sales on “Day-4” for “Street-B”? (Note: Enter the answer rounded to two decimal places. For example, if the answer is “1.234”, then enter it as “1.23”)
Correct answer: 113 (accepted within ±1)
The three figures below (Picture-1, Picture-2, Picture-3) provide the partial regression output from excel for three models (Model-1, Model-2 and Model-3) which were built on the same data (Hint: same number of rows, different number of columns).
Given this information, answer the given subquestions.
ANOVA
| df | SS | MS | F | Significance F | |
|---|---|---|---|---|---|
| Regression | 3 | A1 | 561.9428 | 24.96198 | 0.000867642 |
| Residual | 6 | 135.0717 | 22.51195 | ||
| Total | 9 | 1820.9 |
Picture-1: Partial Results from Excel for Model-1
ANOVA
| df | SS | MS | F | Significance F | |
|---|---|---|---|---|---|
| Regression | 2 | 1685.625 | 43.61254 | 0.000111753 | |
| Residual | 135.275 | ||||
| Total | 9 |
Picture-2: Partial Results from Excel for Model-2
SUMMARY OUTPUT
| Regression Statistics | |
|---|---|
| Multiple R | 0.846545 |
| R Square | 0.716638 |
| Adjusted R Square | 0.681218 |
| Standard Error | 8.030988 |
| Observations | 10 |
ANOVA
| df | SS | MS | F | Significance F | |
|---|---|---|---|---|---|
| Regression | 1 | A2 | 20.23242 | 0.00200727 | |
| Residual | 8 | A3 | |||
| Total | 9 | A4 |
Picture-3: Partial Results from Excel for Model-3
What is the value of “A1”? (Note: Enter the answer rounded to two decimal places. For example, if the answer is “1.234”, then enter it as “1.23”)
Correct answer: 1685.5 (accepted within ±2.5)
The three figures below (Picture-1, Picture-2, Picture-3) provide the partial regression output from excel for three models (Model-1, Model-2 and Model-3) which were built on the same data (Hint: same number of rows, different number of columns).
Given this information, answer the given subquestions.
ANOVA
| df | SS | MS | F | Significance F | |
|---|---|---|---|---|---|
| Regression | 3 | A1 | 561.9428 | 24.96198 | 0.000867642 |
| Residual | 6 | 135.0717 | 22.51195 | ||
| Total | 9 | 1820.9 |
Picture-1: Partial Results from Excel for Model-1
ANOVA
| df | SS | MS | F | Significance F | |
|---|---|---|---|---|---|
| Regression | 2 | 1685.625 | 43.61254 | 0.000111753 | |
| Residual | 135.275 | ||||
| Total | 9 |
Picture-2: Partial Results from Excel for Model-2
SUMMARY OUTPUT
| Regression Statistics | |
|---|---|
| Multiple R | 0.846545 |
| R Square | 0.716638 |
| Adjusted R Square | 0.681218 |
| Standard Error | 8.030988 |
| Observations | 10 |
ANOVA
| df | SS | MS | F | Significance F | |
|---|---|---|---|---|---|
| Regression | 1 | A2 | 20.23242 | 0.00200727 | |
| Residual | 8 | A3 | |||
| Total | 9 | A4 |
Picture-3: Partial Results from Excel for Model-3
What is the value of “A2”? (Note: Enter the answer rounded to two decimal places. For example, if the answer is “1.234”, then enter it as “1.23”)
Correct answer: 1304 (accepted within ±2)
The three figures below (Picture-1, Picture-2, Picture-3) provide the partial regression output from excel for three models (Model-1, Model-2 and Model-3) which were built on the same data (Hint: same number of rows, different number of columns).
Given this information, answer the given subquestions.
ANOVA
| df | SS | MS | F | Significance F | |
|---|---|---|---|---|---|
| Regression | 3 | A1 | 561.9428 | 24.96198 | 0.000867642 |
| Residual | 6 | 135.0717 | 22.51195 | ||
| Total | 9 | 1820.9 |
Picture-1: Partial Results from Excel for Model-1
ANOVA
| df | SS | MS | F | Significance F | |
|---|---|---|---|---|---|
| Regression | 2 | 1685.625 | 43.61254 | 0.000111753 | |
| Residual | 135.275 | ||||
| Total | 9 |
Picture-2: Partial Results from Excel for Model-2
SUMMARY OUTPUT
| Regression Statistics | |
|---|---|
| Multiple R | 0.846545 |
| R Square | 0.716638 |
| Adjusted R Square | 0.681218 |
| Standard Error | 8.030988 |
| Observations | 10 |
ANOVA
| df | SS | MS | F | Significance F | |
|---|---|---|---|---|---|
| Regression | 1 | A2 | 20.23242 | 0.00200727 | |
| Residual | 8 | A3 | |||
| Total | 9 | A4 |
Picture-3: Partial Results from Excel for Model-3
What is the value of “A2”? (Note: Enter the answer rounded to two decimal places. For example, if the answer is “1.234”, then enter it as “1.23”)
Correct answer: 515 (accepted within ±2)
The three figures below (Picture-1, Picture-2, Picture-3) provide the partial regression output from excel for three models (Model-1, Model-2 and Model-3) which were built on the same data (Hint: same number of rows, different number of columns).
Given this information, answer the given subquestions.
ANOVA
| df | SS | MS | F | Significance F | |
|---|---|---|---|---|---|
| Regression | 3 | A1 | 561.9428 | 24.96198 | 0.000867642 |
| Residual | 6 | 135.0717 | 22.51195 | ||
| Total | 9 | 1820.9 |
Picture-1: Partial Results from Excel for Model-1
ANOVA
| df | SS | MS | F | Significance F | |
|---|---|---|---|---|---|
| Regression | 2 | 1685.625 | 43.61254 | 0.000111753 | |
| Residual | 135.275 | ||||
| Total | 9 |
Picture-2: Partial Results from Excel for Model-2
SUMMARY OUTPUT
| Regression Statistics | |
|---|---|
| Multiple R | 0.846545 |
| R Square | 0.716638 |
| Adjusted R Square | 0.681218 |
| Standard Error | 8.030988 |
| Observations | 10 |
ANOVA
| df | SS | MS | F | Significance F | |
|---|---|---|---|---|---|
| Regression | 1 | A2 | 20.23242 | 0.00200727 | |
| Residual | 8 | A3 | |||
| Total | 9 | A4 |
Picture-3: Partial Results from Excel for Model-3
What is the value of “A4”? (Note: Enter the answer rounded to two decimal places. For example, if the answer is “1.234”, then enter it as “1.23”)
Correct answer: 1820.5 (accepted within ±0.5)
The three figures below (Picture-1, Picture-2, Picture-3) provide the partial regression output from excel for three models (Model-1, Model-2 and Model-3) which were built on the same data (Hint: same number of rows, different number of columns).
Given this information, answer the given subquestions.
ANOVA
| df | SS | MS | F | Significance F | |
|---|---|---|---|---|---|
| Regression | 3 | A1 | 561.9428 | 24.96198 | 0.000867642 |
| Residual | 6 | 135.0717 | 22.51195 | ||
| Total | 9 | 1820.9 |
Picture-1: Partial Results from Excel for Model-1
ANOVA
| df | SS | MS | F | Significance F | |
|---|---|---|---|---|---|
| Regression | 2 | 1685.625 | 43.61254 | 0.000111753 | |
| Residual | 135.275 | ||||
| Total | 9 |
Picture-2: Partial Results from Excel for Model-2
SUMMARY OUTPUT
| Regression Statistics | |
|---|---|
| Multiple R | 0.846545 |
| R Square | 0.716638 |
| Adjusted R Square | 0.681218 |
| Standard Error | 8.030988 |
| Observations | 10 |
ANOVA
| df | SS | MS | F | Significance F | |
|---|---|---|---|---|---|
| Regression | 1 | A2 | 20.23242 | 0.00200727 | |
| Residual | 8 | A3 | |||
| Total | 9 | A4 |
Picture-3: Partial Results from Excel for Model-3
What is the value of R-Squared for Model-1? (Note: Enter the answer rounded to two decimal places. For example, if the answer is “1.234”, then enter it as “1.23”. DO NOT CONVERT THE ANSWER TO PERCENTAGE)
Correct answer: 0.88 (accepted within ±0.02)
The three figures below (Picture-1, Picture-2, Picture-3) provide the partial regression output from excel for three models (Model-1, Model-2 and Model-3) which were built on the same data (Hint: same number of rows, different number of columns).
Given this information, answer the given subquestions.
ANOVA
| df | SS | MS | F | Significance F | |
|---|---|---|---|---|---|
| Regression | 3 | A1 | 561.9428 | 24.96198 | 0.000867642 |
| Residual | 6 | 135.0717 | 22.51195 | ||
| Total | 9 | 1820.9 |
Picture-1: Partial Results from Excel for Model-1
ANOVA
| df | SS | MS | F | Significance F | |
|---|---|---|---|---|---|
| Regression | 2 | 1685.625 | 43.61254 | 0.000111753 | |
| Residual | 135.275 | ||||
| Total | 9 |
Picture-2: Partial Results from Excel for Model-2
SUMMARY OUTPUT
| Regression Statistics | |
|---|---|
| Multiple R | 0.846545 |
| R Square | 0.716638 |
| Adjusted R Square | 0.681218 |
| Standard Error | 8.030988 |
| Observations | 10 |
ANOVA
| df | SS | MS | F | Significance F | |
|---|---|---|---|---|---|
| Regression | 1 | A2 | 20.23242 | 0.00200727 | |
| Residual | 8 | A3 | |||
| Total | 9 | A4 |
Picture-3: Partial Results from Excel for Model-3
What is the value of Adjusted R-Square for Model-2? (Note: Enter the answer in rounded to two decimal places. For example, if the answer is “1.234”, then enter it as “1.23”. DO NOT CONVERT THE ANSWER TO PERCENTAGE)
Correct answer: 0.68 (accepted within ±0.02)
The three figures below (Picture-1, Picture-2, Picture-3) provide the partial regression output from excel for three models (Model-1, Model-2 and Model-3) which were built on the same data (Hint: same number of rows, different number of columns).
Given this information, answer the given subquestions.
ANOVA
| df | SS | MS | F | Significance F | |
|---|---|---|---|---|---|
| Regression | 3 | A1 | 561.9428 | 24.96198 | 0.000867642 |
| Residual | 6 | 135.0717 | 22.51195 | ||
| Total | 9 | 1820.9 |
Picture-1: Partial Results from Excel for Model-1
ANOVA
| df | SS | MS | F | Significance F | |
|---|---|---|---|---|---|
| Regression | 2 | 1685.625 | 43.61254 | 0.000111753 | |
| Residual | 135.275 | ||||
| Total | 9 |
Picture-2: Partial Results from Excel for Model-2
SUMMARY OUTPUT
| Regression Statistics | |
|---|---|
| Multiple R | 0.846545 |
| R Square | 0.716638 |
| Adjusted R Square | 0.681218 |
| Standard Error | 8.030988 |
| Observations | 10 |
ANOVA
| df | SS | MS | F | Significance F | |
|---|---|---|---|---|---|
| Regression | 1 | A2 | 20.23242 | 0.00200727 | |
| Residual | 8 | A3 | |||
| Total | 9 | A4 |
Picture-3: Partial Results from Excel for Model-3
Which model is the best model for the provided data?
Model-1
Model-2
Model-3
None of the models
Correct answer
Model-2
A juice shop has been operating in IITM. The price of its most fast-moving juice “The Mango Delight” varies from month to month based on price of mangoes. The price for the juice and the demand for the juice in the past is given in Table-2.
If the demand response curve for “The Mango Delight” is modelled assuming it as “Linear Demand Response” then what is the maximum possible demand? (Note: Enter the answer rounded to two decimal places. For example, if the answer is “1.234”, then enter it as “1.23”)
Correct answer: 2500
A juice shop has been operating in IITM. The price of its most fast-moving juice “The Mango Delight” varies from month to month based on price of mangoes. The price for the juice and the demand for the juice in the past is given in Table-2.
If the demand response curve for “The Mango Delight” is modelled assuming it as “Linear Demand Response” then what is the satiating price? (Note: Enter the answer rounded to two decimal places. For example, if the answer is “1.234”, then enter it as “1.23”)
Correct answer: 125
A juice shop has been operating in IITM. The price of its most fast-moving juice “The Mango Delight” varies from month to month based on price of mangoes. The price for the juice and the demand for the juice in the past is given in Table-2.
What is the difference in elasticity (at a price of Rs. 130/ glass) when modelling the curve as a “Linear Demand Response” as compared to a “Constant Elasticity Curve” (Note: Enter the answer as an absolute number (only magnitude) rounded to two decimal places. For example if the answer is “- 1.2345” then enter it as “1.23”)
Correct answer: 13 (accepted within ±6)
A banking company wants to understand its model performance of a classification problem where the customers who purchased the insurance are labeled as 1 and those not purchased are labeled as 0. Using the table answer the given subquestions.
| S.No | y_pred | y_actual |
|---|---|---|
| 1 | Purchased | Not Purchased |
| 2 | Not Purchased | Not Purchased |
| 3 | Not Purchased | Purchased |
| 4 | Purchased | Purchased |
| 5 | Purchased | Purchased |
| 6 | Purchased | Not Purchased |
| 7 | Purchased | Purchased |
| 8 | Not Purchased | Purchased |
| 9 | Purchased | Not Purchased |
| 10 | Not Purchased | Not Purchased |
| 11 | Not Purchased | Not Purchased |
| 12 | Purchased | Purchased |
What is the accuracy of the model?(in %)
Hint: Round your answer to two decimal places.
Correct answer: 58.35 (accepted within ±0.25)
A banking company wants to understand its model performance of a classification problem where the customers who purchased the insurance are labeled as 1 and those not purchased are labeled as 0. Using the table answer the given subquestions.
| S.No | y_pred | y_actual |
|---|---|---|
| 1 | Purchased | Not Purchased |
| 2 | Not Purchased | Not Purchased |
| 3 | Not Purchased | Purchased |
| 4 | Purchased | Purchased |
| 5 | Purchased | Purchased |
| 6 | Purchased | Not Purchased |
| 7 | Purchased | Purchased |
| 8 | Not Purchased | Purchased |
| 9 | Purchased | Not Purchased |
| 10 | Not Purchased | Not Purchased |
| 11 | Not Purchased | Not Purchased |
| 12 | Purchased | Purchased |
What is the precision of class 1?(in %)
Hint: Round your answer to two decimal places.
Correct answer: 66.65 (accepted within ±0.15)
A banking company wants to understand its model performance of a classification problem where the customers who purchased the insurance are labeled as 1 and those not purchased are labeled as 0. Using the table answer the given subquestions.
| S.No | y_pred | y_actual |
|---|---|---|
| 1 | Purchased | Not Purchased |
| 2 | Not Purchased | Not Purchased |
| 3 | Not Purchased | Purchased |
| 4 | Purchased | Purchased |
| 5 | Purchased | Purchased |
| 6 | Purchased | Not Purchased |
| 7 | Purchased | Purchased |
| 8 | Not Purchased | Purchased |
| 9 | Purchased | Not Purchased |
| 10 | Not Purchased | Not Purchased |
| 11 | Not Purchased | Not Purchased |
| 12 | Purchased | Purchased |
What is the recall of class 1?(in %)
Hint: Round your answer to two decimal places.
Correct answer: 57.2 (accepted within ±0.2)
A banking company wants to understand its model performance of a classification problem where the customers who purchased the insurance are labeled as 1 and those not purchased are labeled as 0. Using the table answer the given subquestions.
| S.No | y_pred | y_actual |
|---|---|---|
| 1 | Purchased | Not Purchased |
| 2 | Not Purchased | Not Purchased |
| 3 | Not Purchased | Purchased |
| 4 | Purchased | Purchased |
| 5 | Purchased | Purchased |
| 6 | Purchased | Not Purchased |
| 7 | Purchased | Purchased |
| 8 | Not Purchased | Purchased |
| 9 | Purchased | Not Purchased |
| 10 | Not Purchased | Not Purchased |
| 11 | Not Purchased | Not Purchased |
| 12 | Purchased | Purchased |
What is the precision of class 0?(in %)
Hint: Round your answer to two decimal places.
Correct answer: 50 (accepted within ±0.1)
A banking company wants to understand its model performance of a classification problem where the customers who purchased the insurance are labeled as 1 and those not purchased are labeled as 0. Using the table answer the given subquestions.
| S.No | y_pred | y_actual |
|---|---|---|
| 1 | Purchased | Not Purchased |
| 2 | Not Purchased | Not Purchased |
| 3 | Not Purchased | Purchased |
| 4 | Purchased | Purchased |
| 5 | Purchased | Purchased |
| 6 | Purchased | Not Purchased |
| 7 | Purchased | Purchased |
| 8 | Not Purchased | Purchased |
| 9 | Purchased | Not Purchased |
| 10 | Not Purchased | Not Purchased |
| 11 | Not Purchased | Not Purchased |
| 12 | Purchased | Purchased |
What is the recall of class 0?(in %)
Hint: Round your answer to two decimal places.
Correct answer: 60 (accepted within ±0.1)
The demand for candy at different prices in the supermarket is specified in the table below. Given this data, answer the given sub-questions (Note: For all the sub-questions, round your answer to two decimal places. Eg: If your answer is 10.256, then round it to 10.26).
| Price | Candy Demand |
|---|---|
| 40 | 500 |
| 60 | 450 |
| 80 | 400 |
| 100 | 350 |
| 120 | 300 |
| 140 | 250 |
If a linear demand-response curve is fit for the data, what is the satiating price?
Correct answer: 240
The demand for candy at different prices in the supermarket is specified in the table below. Given this data, answer the given sub-questions (Note: For all the sub-questions, round your answer to two decimal places. Eg: If your answer is 10.256, then round it to 10.26).
| Price | Candy Demand |
|---|---|
| 40 | 500 |
| 60 | 450 |
| 80 | 400 |
| 100 | 350 |
| 120 | 300 |
| 140 | 250 |
If a linear demand-response curve is fit for the data, what is the market size?
Correct answer: 600
The demand for candy at different prices in the supermarket is specified in the table below. Given this data, answer the given sub-questions (Note: For all the sub-questions, round your answer to two decimal places. Eg: If your answer is 10.256, then round it to 10.26).
| Price | Candy Demand |
|---|---|
| 40 | 500 |
| 60 | 450 |
| 80 | 400 |
| 100 | 350 |
| 120 | 300 |
| 140 | 250 |
What is the elasticity of the linear demand-response curve, when the price is Rs. 140?
Correct answer: 1.4