GATE AE 2025 • Q10 MCQ • 2 Marks

General Aptitude

Analytical & Spatial Aptitude

Subtopic: Analogy & Shape Transformation

Question Statement:

The number of patients per shift ( X) consulting Dr. Gita in her past 100 shifts is shown in the figure. If the amount she earns is ₹ 1000(X - 0.2), what is the average amount (in ₹) she has earned per shift in the past 100 shifts? Note: The figure shown is representative.

Options:

  • (A) 6,100
  • (B) 6,300
  • (C) 6,000
  • (D) 6,500 20 40 30 10 0 10 20 30 40 50 5 6 7 8 Number of shifts Number of patients per shift (X)

Official Answer Key:

A

Step-by-Step Solution & Explanation

### **Detailed Step-by-Step Solution (GATE AE 2025 Q.10)** **1. Intuitive Physical Setup & Given Parameters**: A bar chart shows the distribution of the number of patients $X$ per shift seen by Dr. Gita over $N = 100$ shifts: - $X = 5$ patients: 20 shifts - $X = 6$ patients: 40 shifts - $X = 7$ patients: 30 shifts - $X = 8$ patients: 10 shifts - Total shifts: $20 + 40 + 30 + 10 = 100$ Earning formula per shift: $\text{Earning}(X) = ₹\,1000(X - 0.2)$ We need to find her **average earning per shift** over the past 100 shifts. **2. Step-by-Step Statistical Derivation**: 1. **Compute Average Number of Patients per Shift ($\bar{X}$)**: $\bar{X} = \frac{\sum (X_i \times f_i)}{N} = \frac{(5 \times 20) + (6 \times 40) + (7 \times 30) + (8 \times 10)}{100}$ $\sum (X_i f_i) = 100 + 240 + 210 + 80 = 630\text{ patients}$ $\bar{X} = \frac{630}{100} = 6.3\text{ patients/shift}$ 2. **Compute Average Earning**: Using the linearity of the expectation operator $E[aX + b] = a E[X] + b$: $\text{Average Earning} = 1000(\bar{X} - 0.2)$ $\text{Average Earning} = 1000(6.3 - 0.2) = 1000(6.1) = ₹\,6,100$ **3. Comprehensive Options & Distractor Analysis**: - **(A) 6,100**: ✅ **CORRECT**. $1000(6.3 - 0.2) = ₹\,6,100$. - **(B) 6,300**: ❌ **INCORRECT**. Forgets the subtraction of $0.2$ ($1000 \times 6.3$). - **(C) 6,000**: ❌ **INCORRECT**. Rounding error. - **(D) 6,500**: ❌ **INCORRECT**. Unweighted arithmetic average of $\{5, 6, 7, 8\} = 6.5$. **4. Official Master Key & Exam Takeaway**: - **Official Answer Key**: **A** - **Exam Takeaway**: By linearity of expectation, calculate the weighted mean $\bar{X} = 6.3$ first, then evaluate the linear cost function $E[1000(X - 0.2)] = 1000(6.3 - 0.2) = 6100$.

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