Law Entrance - Quantitative Techniques & Data Analysis Previous Year Questions (PYQ)

Q1.

[CLAT Quantitative Techniques - Averages, Mixtures & Allegations (Question #32)]
Caselet: A Lok Adalat bench was assigned 600 motor accident claim petitions. Through mutual settlement conciliation, 30% of the claims were resolved amicably on day one. How many claim petitions were settled amicably on day one?

(A)

{'key': 'A', 'text': '180 claims'}

(B)

{'key': 'B', 'text': '195 claims'}

(C)

{'key': 'C', 'text': '160 claims'}

(D)

{'key': 'D', 'text': '210 claims'}

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Q2.

[CLAT Quantitative Techniques - Simple & Compound Interest Calculations (Question #24)]
Caselet: A Lok Adalat bench was assigned 800 motor accident claim petitions. Through mutual settlement conciliation, 70% of the claims were resolved amicably on day one. How many claim petitions were settled amicably on day one?

(A)

{'key': 'A', 'text': '560 claims'}

(B)

{'key': 'B', 'text': '575 claims'}

(C)

{'key': 'C', 'text': '540 claims'}

(D)

{'key': 'D', 'text': '590 claims'}

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Q1.

Strategic & Logical Decision-Making: In critical evaluation of 'Core Jurisprudence - Tabular & Numerical Caselet Passages', which analytical deduction represents valid inference under the given premise?

(A)

A conclusion necessarily necessitated by stated factual premises without unverified extraneous assumptions (Core Jurisprudence - Tabular & Numerical Caselet Passages)

(B)

An inductive generalization derived solely from an isolated anomalous data point

(C)

A circular assertion that assumes the contested premise as its own conclusion

(D)

A correlation mistakenly treated as direct irrefutable causality without confounding control

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Q2.

Passage: In the Supreme Court of India, a special constitution bench evaluated 250 pending public interest litigations (PILs). 40% of the PILs pertained to environmental violations, 35% concerned educational reforms, and the remaining 25% addressed prison reforms. Among the environmental PILs, 60% were disposed of within six months.
How many environmental PILs were disposed of within six months?

(A)

{'key': 'A', 'text': '50 PILs'}

(B)

{'key': 'B', 'text': '60 PILs'}

(C)

{'key': 'C', 'text': '75 PILs'}

(D)

{'key': 'D', 'text': '90 PILs'}

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Q1.

[CLAT Quantitative Techniques - Simple & Compound Interest Calculations (Question #78)]
Caselet: A Lok Adalat bench was assigned 1200 motor accident claim petitions. Through mutual settlement conciliation, 70% of the claims were resolved amicably on day one. How many claim petitions were settled amicably on day one?

(A)

{'key': 'A', 'text': '840 claims'}

(B)

{'key': 'B', 'text': '855 claims'}

(C)

{'key': 'C', 'text': '820 claims'}

(D)

{'key': 'D', 'text': '870 claims'}

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Q2.

[CLAT Quantitative Techniques - Averages, Mixtures & Allegations (Question #38)]
Caselet: A Lok Adalat bench was assigned 1200 motor accident claim petitions. Through mutual settlement conciliation, 30% of the claims were resolved amicably on day one. How many claim petitions were settled amicably on day one?

(A)

{'key': 'A', 'text': '360 claims'}

(B)

{'key': 'B', 'text': '375 claims'}

(C)

{'key': 'C', 'text': '340 claims'}

(D)

{'key': 'D', 'text': '390 claims'}

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Q1.

[CLAT Quantitative Techniques - Comparative Statistical & Ratio Analysis (Question #77)]
Caselet: A Lok Adalat bench was assigned 1100 motor accident claim petitions. Through mutual settlement conciliation, 60% of the claims were resolved amicably on day one. How many claim petitions were settled amicably on day one?

(A)

{'key': 'A', 'text': '660 claims'}

(B)

{'key': 'B', 'text': '675 claims'}

(C)

{'key': 'C', 'text': '640 claims'}

(D)

{'key': 'D', 'text': '690 claims'}

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Q2.

Passage: In the Supreme Court of India, a special constitution bench evaluated 250 pending public interest litigations (PILs). 40% of the PILs pertained to environmental violations, 35% concerned educational reforms, and the remaining 25% addressed prison reforms. Among the environmental PILs, 60% were disposed of within six months.
How many environmental PILs were disposed of within six months?

(A)

{'key': 'A', 'text': '50 PILs'}

(B)

{'key': 'B', 'text': '60 PILs'}

(C)

{'key': 'C', 'text': '75 PILs'}

(D)

{'key': 'D', 'text': '90 PILs'}

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Q1.

[CLAT Quantitative Techniques - Time, Work & Speed Calculations (Question #28)]
Caselet: A Lok Adalat bench was assigned 1200 motor accident claim petitions. Through mutual settlement conciliation, 50% of the claims were resolved amicably on day one. How many claim petitions were settled amicably on day one?

(A)

{'key': 'A', 'text': '600 claims'}

(B)

{'key': 'B', 'text': '615 claims'}

(C)

{'key': 'C', 'text': '580 claims'}

(D)

{'key': 'D', 'text': '630 claims'}

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Q2.

[CLAT Quantitative Techniques - Simple & Compound Interest Calculations (Question #60)]
Caselet: A Lok Adalat bench was assigned 1400 motor accident claim petitions. Through mutual settlement conciliation, 70% of the claims were resolved amicably on day one. How many claim petitions were settled amicably on day one?

(A)

{'key': 'A', 'text': '980 claims'}

(B)

{'key': 'B', 'text': '995 claims'}

(C)

{'key': 'C', 'text': '960 claims'}

(D)

{'key': 'D', 'text': '1010 claims'}

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Q1.

[CLAT Quantitative Techniques - Tabular & Numerical Caselet Passages (Question #19)]
Caselet: A Lok Adalat bench was assigned 1300 motor accident claim petitions. Through mutual settlement conciliation, 20% of the claims were resolved amicably on day one. How many claim petitions were settled amicably on day one?

(A)

{'key': 'A', 'text': '260 claims'}

(B)

{'key': 'B', 'text': '275 claims'}

(C)

{'key': 'C', 'text': '240 claims'}

(D)

{'key': 'D', 'text': '290 claims'}

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Q2.

[CLAT Quantitative Techniques - Comparative Statistical & Ratio Analysis (Question #59)]
Caselet: A Lok Adalat bench was assigned 1300 motor accident claim petitions. Through mutual settlement conciliation, 60% of the claims were resolved amicably on day one. How many claim petitions were settled amicably on day one?

(A)

{'key': 'A', 'text': '780 claims'}

(B)

{'key': 'B', 'text': '795 claims'}

(C)

{'key': 'C', 'text': '760 claims'}

(D)

{'key': 'D', 'text': '810 claims'}

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Q1.

[CLAT Quantitative Techniques - Time, Work & Speed Calculations (Question #58)]
Caselet: A Lok Adalat bench was assigned 1200 motor accident claim petitions. Through mutual settlement conciliation, 50% of the claims were resolved amicably on day one. How many claim petitions were settled amicably on day one?

(A)

{'key': 'A', 'text': '600 claims'}

(B)

{'key': 'B', 'text': '615 claims'}

(C)

{'key': 'C', 'text': '580 claims'}

(D)

{'key': 'D', 'text': '630 claims'}

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Q2.

[CLAT Quantitative Techniques - Averages, Mixtures & Allegations (Question #26)]
Caselet: A Lok Adalat bench was assigned 1000 motor accident claim petitions. Through mutual settlement conciliation, 30% of the claims were resolved amicably on day one. How many claim petitions were settled amicably on day one?

(A)

{'key': 'A', 'text': '300 claims'}

(B)

{'key': 'B', 'text': '315 claims'}

(C)

{'key': 'C', 'text': '280 claims'}

(D)

{'key': 'D', 'text': '330 claims'}

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Q1.

[CLAT Quantitative Techniques - Percentage, Profit-Loss & Growth Trends (Question #57)]
Caselet: A Lok Adalat bench was assigned 1100 motor accident claim petitions. Through mutual settlement conciliation, 40% of the claims were resolved amicably on day one. How many claim petitions were settled amicably on day one?

(A)

{'key': 'A', 'text': '440 claims'}

(B)

{'key': 'B', 'text': '455 claims'}

(C)

{'key': 'C', 'text': '420 claims'}

(D)

{'key': 'D', 'text': '470 claims'}

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Q2.

[CLAT Quantitative Techniques - Tabular & Numerical Caselet Passages (Question #1)]
Caselet: A Lok Adalat bench was assigned 500 motor accident claim petitions. Through mutual settlement conciliation, 20% of the claims were resolved amicably on day one. How many claim petitions were settled amicably on day one?

(A)

{'key': 'A', 'text': '100 claims'}

(B)

{'key': 'B', 'text': '115 claims'}

(C)

{'key': 'C', 'text': '80 claims'}

(D)

{'key': 'D', 'text': '130 claims'}

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Law Entrance - Quantitative Techniques & Data Analysis previous year questions (PYQ)

2025 (9 questions)

2024 (23 questions)

2023 (11 questions)

2022 (11 questions)

2021 (10 questions)

2020 (10 questions)

2019 (10 questions)

2018 (10 questions)

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