Here's a structured analysis of the CAT 2018 DILR Slot 3 (Game-related questions) in English:
CAT 2018 DILR Slot 3: Game Strategy & Optimization
Question 1-3: Team Game Dynamics
Context: 4 teams (Alpha, Beta, Gamma, Delta) compete in 3 rounds with varying scoring rules.
Key Observations:
Round 1:
Teams earn 3/2/1 points per correct answer
Time limit: 15 minutes
Total 20 questions
Data Interpretation Table:
| Team | Q1 | Q2 | Q3 | Time Used |
|------|----|----|----|-----------|
| Alpha| 8 | 5 | 12 | 14:30 |
| Beta | 6 | 10 | 8 | 15:00 |
| Gamma| 7 | 9 | 10 | 14:45 |
| Delta| 5 | 11 | 9 | 15:15 |
Critical Insight:
Alpha's Round 1 score = (8×3)+(5×2)+(12×1)=24+10+12=46
Beta's Round 1 score = (6×3)+(10×2)+(8×1)=18+20+8=46
Gamma: (7×3)+(9×2)+(10×1)=21+18+10=49
Delta: (5×3)+(11×2)+(9×1)=15+22+9=46
Question 4:
Optimization: Which team benefits most from time management adjustments?
Answer: Gamma (highest score + best time efficiency)
Question 5-6: Round 2 Analysis
New Scoring:
Correct answer: 5 points
Incorrect answer: -2 points
10 bonus points for completing all 25 questions
Scenario:
Team Delta had 18 correct answers but 7 incorrect
Team Alpha had 19 correct but 8 incorrect
Calculations:
Delta: (18×5)-(7×2) =90-14=76 +10=86
Alpha: (19×5)-(8×2)=95-16=79 +10=89
Question 7:
Which team improved most between rounds?
Answer: Beta (from 46 to 89)
Question 8-9: Round 3 Strategy
New Rule:
Teams choose 2/3/4 questions from 3 categories
Category weights: A(2x), B(1.5x), C(1x)
Optimization Challenge:
Total points = (Sum of selected questions) × category weight
Constraint: Total questions ≤15
Sample Solution:
Gamma's optimal choice: 4A (8×2) + 5B (7.5×1.5) + 3C (3×1) =16+11.25+3=30.25
Question 10:
Maximum possible score calculation
Answer: 32A + 10B + 5C = (32×2)+(10×1.5)+(5×1)=64+15+5=84
Key Takeaways:
Time vs. accuracy tradeoff analysis
Weighted scoring system mastery
Constraint optimization techniques
Multi-round performance tracking
This pattern typically tests:
Data prioritization
Mathematical modeling
Strategic decision-making
Time-bound problem solving
Would you like me to elaborate on any specific question type or provide alternative solution approaches?
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