Which of the following inferences is best supported by the data in the table?
Which of the following inferences is best supported by the data in the table?
Options
Official answer
Option (B) is correct — the table shows overspeeding at 56%, by far the largest single cause of road accidents in India (2023), so it is correctly identified as 'the key issue' needing both technological (speed cameras, iRASTE-type alerts) and behavioural (driver discipline) fixes.
Marking scheme
- 1.1 mark for selecting option (B); no marks for any other option since the data does not support them.
- 2.No partial credit for MCQs — the answer is either fully correct or incorrect.
Hint
Compare the percentages directly: overspeeding (56%) dwarfs every other cause, so the correct inference must centre on that.
Quick oral answer
Overspeeding is 56% of the table, far higher than any other cause, so the data-supported inference is that speeding is the key issue needing both technology and behaviour change — not helmet rules, mobile use trends, or drunk driving, which the numbers don't support.
Common mistakes
- 1.Choosing (D) without adding 15% + 6% = 21% and comparing it to drunk driving's 8% — a simple arithmetic check that rules this option out.
- 2.Choosing (C) because 'mobile phones' feels like a modern, dramatic cause, ignoring that the table gives no year-on-year trend data to support 'fastest growing'.
- 3.Treating any true-sounding statement as correct instead of checking which one the numeric data specifically and uniquely supports.
Analysis and explanation
This question tests data interpretation — picking the inference the numbers actually support, not just any plausible-sounding statement.
Why (B) is correct: Overspeeding accounts for 56% of accidents, more than all other causes combined. The passage itself (para 4) discusses AI-based technological interventions (iRASTE, automated cameras) alongside personal responsibility (behavioural change), so 'technological and behavioural interventions' is the exact combination the passage recommends for this dominant cause.
Why the distractors fail:
- (A) is wrong because 'no helmet/seat belt' is only 15%, well below overspeeding's 56% — it is A cause, not THE cause the data most strongly supports.
- (C) is wrong because the table gives no data on trend/growth rate over time; 'fastest growing' is an inference the static 2023 snapshot cannot support, and distraction (mobiles) is only 6%, the second-smallest category.
- (D) is wrong arithmetically: drunk driving (8%) is less than 'no helmet/seat belt' (15%) alone, let alone combined with distraction (6%), so 8% is far less than 21%.
Exam trap: Table-based MCQs often include one option that sounds analytically sophisticated (like C's 'fastest growing') but requires data the table simply does not provide — always check whether the claimed comparison is actually calculable from the given numbers.
Interesting facts
In real Ministry of Road Transport and Highways data for 2022, overspeeding was similarly reported as the single largest contributing factor, accounting for over 60% of fatal road accidents in India.
Table/graphic-based inference questions were introduced into CBSE English Core reading sections as part of the shift towards 'competency-based' assessment recommended by NEP 2020.
iRASTE (Integrated Road Accident and Safety Technology Enhancement), referenced in the passage, is a real Nagpur-based pilot project by WRI India and Intel using AI cameras to reduce accidents.
Question details
Q18 of 29 questions
- Board
- CBSE
- Class
- Class 12
- Subject
- English Core
- Year
- 2026
- Section
- Section A
- Marks
- 1
- Type
- MCQ
- Chapter
- Reading Comprehension — Unseen Passage (CBSE Class 12 English Core, Section A)
- Topic
- Data interpretation from the road accidents table
- Bloom's level
- analyze
- Syllabus topic
- Section A: Reading Skills — Interpreting data/graphics embedded in an unseen passage
- Author
- CBSE
- Reviewed by
- Padhantu Academic Team
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Frequently asked questions
Why is drunk driving not the answer even though it sounds serious?
Because at only 8%, drunk driving is numerically smaller than 'no helmet/seat belt' (15%) alone, and far smaller than overspeeding (56%). The correct inference must be backed by the actual percentages, not by how serious a cause sounds.
How should I approach table-based inference MCQs in the exam?
Convert each option into a testable numeric claim and check it against the table: identify the largest value, verify any addition/comparison claims, and reject any option (like a 'trend' claim) that needs data the table does not provide.