CAT and MBA Entrance Preparation Module 2 – Verbal Ability and Reading Comprehension (VARC)
Grammar and error spotting: MBA entrance tests
Find errors of agreement, tense, pronouns, modifiers, lists and prepositions with six checks in a fixed order, and fix each with the smallest change.
What you will learn
- Detect errors of agreement, tense, pronouns and prepositions in test sentences
- Correct a sentence with the smallest change that makes it right
- Identify the tests whose official topic lists name grammar
- Explain why an option that rewrites more than the error is usually a distractor
Before you start
What you’ll learn · Before you start
What you will learn
- Detect errors of agreement, tense, pronouns and prepositions in test sentences
- Correct a sentence with the smallest change that makes it right
- Identify the tests whose official topic lists name grammar
- Explain why an option that rewrites more than the error is usually a distractor
Before you start
On this page
NMAT gives its Language Skills section 36 questions in 28 minutes, about 47 seconds each, and lists Error Identification and Prepositions among its topics. At that pace there is time to read a sentence once for each kind of error, in a fixed order, but not to reread it until something sounds wrong.
This lesson names the tests whose documents list grammar, runs six checks in order on every sentence, and fixes each error with the smallest change that makes it right, which is also how a correction question’s wrong options give themselves away.
Five tests name their English sections differently
The tests’ own documents decide what is worth practising, and they do not use the same words:
| Test | What its document names | Where, and how many questions |
|---|---|---|
| NMAT 2026 | Error Identification, Prepositions, Sentence Completion | Language Skills: 36 in 28 minutes |
| XAT 2026 | English grammar, beside vocabulary, para jumbles and cloze tests | Verbal Ability and Logical Reasoning: 26 |
| SNAP 2026 | General English, as a section name | 10 of the test’s 60 questions |
| CMAT 2026 | Language Comprehension, as a section name | 20 questions of 4 marks each |
| MAT | Language Comprehension, as a section name | 30 of its 150 questions |
Only NMAT names error spotting: A question that gives a sentence, usually in marked parts, and asks which part holds a grammatical error, or whether it has none. NMAT names it Error Identification. outright, as Error Identification, and only XAT says English grammar; SNAP, CMAT and MAT name a section and list nothing inside it. CAT’s FAQs say it has no defined syllabus, so nothing in this lesson is a claim about grammar questions in CAT.
Not affiliated
MySmartCoPilot is not affiliated with GMAC, XLRI, Symbiosis International University, the National Testing Agency, AIMA or the IIMs. Each test is described only from its own documents, and every sentence here is original.
Checkpoint
Check: The tests that name grammar
Check in a fixed order, the verb first
A sentence read for whatever sounds wrong gives up its loudest error and hides the quiet one. Six checks in a fixed order find both: the subject and its verb, a tense against its time word, each pronoun, each modifier and its subject, every list, and last the preposition each word takes. A failed check sends the sentence to be fixed, and the fixed sentence starts again at check 1. Step through a sentence with two errors:
The drawing shows the whole scene; its 9 steps are listed below.
Every step as text
- The sentence. 'Walking into the hall, the clock between the windows were showing ten past nine.' Read it once for each check, in order, instead of rereading it for whatever sounds wrong.
- 1. Subject and verb. The subject is 'the clock'; 'between the windows' only describes it. A singular subject takes 'was', so check 1 fails at 'were'.
- Fix one span. Mark 'were showing' and make the smallest change that is right, 'was showing'. Then the fixed sentence goes back to check 1, because one fix can disturb another check.
- Back to check 1. 'The clock between the windows was showing' agrees: check 1 passes this time.
- 2. Tense and time word. 'Was showing ten past nine' describes a past moment, and no time word clashes with it. Check 2 passes.
- 3. Pronoun. There is no pronoun in the sentence, so check 3 has nothing to test and passes.
- 4. Modifier and subject. 'Walking into the hall' needs a subject that can walk, and the main clause gives it 'the clock'. Check 4 fails: the person who walked is missing.
- Fix one span again. Replace 'the clock between the windows was showing' with 'I saw that the clock between the windows showed'. The participle now has 'I' as its subject, and the sentence goes back to check 1.
- All six checks pass. 'I saw' agrees and fits the past, no pronoun lacks its noun, 'Walking' belongs to 'I', there is no list, and 'saw that' takes no preposition. The sentence is right.
Each check rests on a rule a grammar states. The verb takes the person and number of its subject, which is subject–verb agreement: The rule that a verb takes the person and number of its subject: 'The list of documents is printed', because the subject is 'list', not the noun beside the verb. (English Grammar Today); a finished time such as “two weeks ago” takes the past simple, not the present perfect; a participle clause normally shares the main clause’s subject, and one that does not is a dangling modifier: An opening phrase, such as 'Walking into the hall', whose understood subject is not the subject of the main clause, so the sentence says the wrong thing did the action.; and every item of a list keeps one form, which is parallel structure: Using the same grammatical form for the items of a list or a pair: three -ing forms, three infinitives or three nouns, not a mixture. (Purdue OWL). Here is one sentence for each check, with its smallest fix:
"""Six checks in a fixed order, one sentence with one error for each, and the smallest fix of each error.
For every sentence the program applies the fix, confirms that the fix changes no word outside the wrong span, and
reports the check that catches the error and the checks it passed first. Put a sentence of your own in
SENTENCES, with its wrong span and its fix, and run it again.
"""
CHECKS = ["subject and verb", "tense and time word", "pronoun", "modifier and its subject", "lists in one form",
"preposition and idiom"]
# (sentence, the wrong span, its fix, the number of the check that catches it)
SENTENCES = [
("The list of documents that every candidate must carry to the centre are printed on the admit card.",
"are", "is", 1),
("The institute has announced the results two weeks ago.", "has announced", "announced", 2),
("The difference between my sister and I was two marks.", "and I", "and me", 3),
("Walking into the hall, the clock showed ten past nine.", "the clock showed", "I saw that the clock showed", 4),
("The plan asks you to read daily, to solve a set each week and taking a paper every month.", "taking",
"to take", 5),
("The panel discussed about her work experience for ten minutes.", "discussed about", "discussed", 6),
]
def changed_region(before, after):
"""The words of `before` that differ from `after`, found by stripping the words both share at each end."""
a, b = before.split(), after.split()
p = 0
while p < min(len(a), len(b)) and a[p] == b[p]:
p += 1
s = 0
while s < min(len(a), len(b)) - p and a[-1 - s] == b[-1 - s]:
s += 1
return p, len(a) - s
def inside_wrong_span(sentence, wrong, fixed):
"""True when the fix changes no word outside the wrong span."""
words, target = sentence.split(), wrong.split()
starts = [i for i in range(len(words) - len(target) + 1) if words[i:i + len(target)] == target]
assert len(starts) == 1, f"the wrong span must occur once as whole words: {wrong!r}"
start, end = changed_region(sentence, fixed)
return starts[0] <= start and end <= starts[0] + len(target)
tally = {name: 0 for name in CHECKS}
for sentence, wrong, fix, check in SENTENCES:
fixed = sentence.replace(wrong, fix)
only = inside_wrong_span(sentence, wrong, fixed)
tally[CHECKS[check - 1]] += 1
passed = ", ".join(str(n) for n in range(1, check)) or "none"
print(f"Check {check}, {CHECKS[check - 1]} (passed first: {passed})")
print(f" {sentence}")
print(f" {wrong!r} -> {fix!r}: " + ("nothing outside the wrong span changes" if only else "words outside it change"))
print(f" {fixed}")
print()
print("Caught at each check: " + ", ".join(f"{n} {name}" for name, n in tally.items()))
single = all(inside_wrong_span(s, w, s.replace(w, f)) for s, w, f, _ in SENTENCES)
print("Every fix changes only its wrong span." if single else "A fix changes words outside its wrong span.")Output
Check 1, subject and verb (passed first: none) The list of documents that every candidate must carry to the centre are printed on the admit card. 'are' -> 'is': nothing outside the wrong span changes The list of documents that every candidate must carry to the centre is printed on the admit card. Check 2, tense and time word (passed first: 1) The institute has announced the results two weeks ago. 'has announced' -> 'announced': nothing outside the wrong span changes The institute announced the results two weeks ago. Check 3, pronoun (passed first: 1, 2) The difference between my sister and I was two marks. 'and I' -> 'and me': nothing outside the wrong span changes The difference between my sister and me was two marks. Check 4, modifier and its subject (passed first: 1, 2, 3) Walking into the hall, the clock showed ten past nine. 'the clock showed' -> 'I saw that the clock showed': nothing outside the wrong span changes Walking into the hall, I saw that the clock showed ten past nine. Check 5, lists in one form (passed first: 1, 2, 3, 4) The plan asks you to read daily, to solve a set each week and taking a paper every month. 'taking' -> 'to take': nothing outside the wrong span changes The plan asks you to read daily, to solve a set each week and to take a paper every month. Check 6, preposition and idiom (passed first: 1, 2, 3, 4, 5) The panel discussed about her work experience for ten minutes. 'discussed about' -> 'discussed': nothing outside the wrong span changes The panel discussed her work experience for ten minutes. Caught at each check: 1 subject and verb, 1 tense and time word, 1 pronoun, 1 modifier and its subject, 1 lists in one form, 1 preposition and idiom Every fix changes only its wrong span.
Recorded with Python 3.14.8 on macOS 26 arm64. To run it yourself: mise exec python@3.14.8 -- python3 checks.py
Runs on this device, in your browser. The first run downloads Python (about 13.5 MB), which is kept for the next runs.
Your run, in this browser
Agreeing the verb with the nearest noun
In “The list of documents … are printed”, the noun beside the verb is “centre” and the one before that “documents”, but the subject is “list”. Find the subject by asking what is printed, then make the verb agree with it.
Each error is caught at its own check, after the checks before it passed. Put a sentence of your own in SENTENCES,
with its wrong span and its fix, and run the program again.
Key idea
Read a sentence once for each check, in a fixed order, the verb first and prepositions last, and send every fixed sentence back to check 1.
Checkpoint
Check: Six checks in a fixed order
The smallest change that makes it right
A correction question offers several versions of a sentence. Two tests decide it, in this order: the option must be right, and of the right options the one that changes least is the answer, because a longer rewrite tends to bring a new error or a new meaning with it. The program counts what four corrections change:
"""Four corrections of one sentence: how much of the sentence each one changes.
The sentence has one error, a plural verb after "Neither of …". The program lists the spans each option changes; the
lesson judges which option fixes the error without changing anything else. Add an option of your own to OPTIONS and
run it again.
"""
import difflib
SENTENCE = "Neither of the two brochures mention the deadline."
OPTIONS = {
"a": "Neither of the two brochures mentions the deadline.",
"b": "Neither of the two brochures do mention the deadline.",
"c": "The deadline is mentioned in neither of the two brochures, which is a problem.",
"d": "Both the brochures do not mention the deadline.",
}
def spans(before, after):
"""The spans of words that differ between two sentences, and the number of words in them."""
a, b = before.split(), after.split()
ops = difflib.SequenceMatcher(a=a, b=b, autojunk=False).get_opcodes()
out = [(" ".join(a[i1:i2]) or "-", " ".join(b[j1:j2]) or "-") for op, i1, i2, j1, j2 in ops if op != "equal"]
words = sum(max(i2 - i1, j2 - j1) for op, i1, i2, j1, j2 in ops if op != "equal")
return out, words
print(f"Sentence: {SENTENCE}")
print()
for name, option in OPTIONS.items():
changed, words = spans(SENTENCE, option)
print(f"({name}) {option}")
print(f" {len(changed)} span{'' if len(changed) == 1 else 's'}, {words} word{'' if words == 1 else 's'} changed: "
+ "; ".join(f"{old!r} -> {new!r}" for old, new in changed))
least = min(spans(SENTENCE, o)[1] for o in OPTIONS.values())
fewest = [n for n, o in OPTIONS.items() if spans(SENTENCE, o)[1] == least]
print()
print(f"Fewest words changed ({least}): " + ", ".join(f"({n})" for n in fewest))Output
Sentence: Neither of the two brochures mention the deadline.
(a) Neither of the two brochures mentions the deadline.
1 span, 1 word changed: 'mention' -> 'mentions'
(b) Neither of the two brochures do mention the deadline.
1 span, 1 word changed: '-' -> 'do'
(c) The deadline is mentioned in neither of the two brochures, which is a problem.
2 spans, 11 words changed: 'Neither' -> 'The deadline is mentioned in neither'; 'brochures mention the deadline.' -> 'brochures, which is a problem.'
(d) Both the brochures do not mention the deadline.
3 spans, 5 words changed: 'Neither of' -> 'Both'; 'two' -> '-'; '-' -> 'do not'
Fewest words changed (1): (a), (b)
Recorded with Python 3.14.8 on macOS 26 arm64. To run it yourself: mise exec python@3.14.8 -- python3 options.py
Runs on this device, in your browser. The first run downloads Python (about 13.5 MB), which is kept for the next runs.
Your run, in this browser
(a) and (b) each change one word, but only (a) is right: in formal writing “Neither of” takes a singular verb (English Grammar Today), and (b)’s “do mention” is still plural. (c) changes 11 words and adds “which is a problem”, a judgement the sentence never made; (d) turns “neither” into “both … not”, which can mean that only one brochure is silent.
Standard written English, and Indian English
The tests’ documents name no variety of English. MySmartCoPilot’s recommendation is to choose the form that standard written English uses; where Indian English usage differs, the aptitude lesson on Indian English usage explains the difference.
Checkpoint
Check: The smallest change that makes it right
Practise: checks in order and the smallest fix
Ten questions on the tests’ lists, the six checks and the smallest change follow, starting with the idea you have answered least well.
Practice that adapts to you
Practise this lesson
10 questions about 5 ideas of this lesson. Each answer is explained at once, and what you get right is kept in this browser.
Twenty-four test sentences, fully corrected Pro: opens with a Pro, Premium or Ultimate pass
Four sentences for each of the six checks, every one original, each with its wrong span, its fix and the trap that hides it. A program confirms that every fix changes nothing outside its wrong span.
In this part:
- Checks 1 and 2: subjects, verbs and time words, worked
- Checks 3 and 4: pronoun forms and modifiers, worked
- Checks 5 and 6: lists and the words verbs take, worked
- The bank, checked and counted
1 runnable example (Python) · about 5 minutes
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Preposition and idiom drills, with the reason for each Pro: opens with a Pro, Premium or Ultimate pass
Twelve slips with the word each verb or adjective takes, every one from its entry in the Oxford Advanced Learner’s Dictionary. Nine use the wrong preposition, and three use the wrong form after the right word.
In this part:
- Twelve slips, each with the dictionary’s pattern
- Agree with, agree to and agree on: three meanings from one verb
- Patterns the dictionary also allows
- A drill for the patterns you miss
1 runnable example (Python) · about 4 minutes
Opening this part with your pass…
This part opens with any MySmartCoPilot pass.
- Pro pass · 1 week₹79$2.99
- 30 days₹179$5.99
- 1 year₹1,699$45
One payment; a pass never renews. The price shown is the total you pay: no fees or charges are added at checkout.
Passes can’t be bought right now, so this part can’t be opened at the moment. The free part above stands on its own. If you have a pass, enter your licence key.
It also opens every other in-depth part in Learn and every Pro tool. Sales are final, except where the law gives you a right to withdraw, for example in the EU and the UK (refund policy).
Interview questions
-
Fresher to mid
An error-spotting sentence in marked parts seems to hold errors in two parts, but only one answer is allowed. How do you decide which part to mark, and what does a fixed order of checks add?
-
Fresher to mid
In a sentence-correction question, two options are grammatical: one changes only the error, the other rewrites the sentence and reads better. Which do you choose, and when could the rewrite be the right answer?
-
Fresher to mid
A test sentence says "The panel will discuss about the cut-offs", which you hear every day. Do you mark it as the error, given that the tests' documents name no variety of English? Defend your choice.
Flashcards · 6 cards
Recall it, then check
Say the answer to yourself before you look: recalling it is what makes it stick.
-
Which MBA tests' documents name grammar or error spotting?
NMAT 2026 lists Error Identification, Prepositions and Sentence Completion, and XAT 2026 names English grammar. SNAP, CMAT and MAT name a language section with no topic list, and CAT has no defined syllabus.
-
How much time a question does NMAT's Language Skills section give?
36 questions in 28 minutes, about 47 seconds each: time to read a sentence once for each kind of error, in a fixed order, but not to reread it until something sounds wrong.
-
What are the six error-spotting checks, in order?
Subject and verb; a tense against its time word; each pronoun; each modifier and its subject; every list; and last each preposition. After a fix the sentence starts again at check 1.
-
How do you avoid agreeing a verb with the nearest noun?
Find the subject by asking what does the action. In "The list of documents … are printed", what is printed is the list, so the verb is "is".
-
What are a dangling modifier and a break in parallel structure?
A dangling modifier is a participle clause that does not share the main clause's subject. A list breaks parallel structure when its items switch form; every item should keep one form.
-
Of several corrections that are right, which is the answer?
The correct option with the fewest changes, because a bigger rewrite tends to add a new error or a new meaning. For "Neither of the two brochures mention …", the answer changes one word: "mentions".
Key takeaways
- NMAT names Error Identification and Prepositions, XAT names English grammar, and SNAP, CMAT and MAT name a language section with no topic list.
- In error spotting, six checks in a fixed order, the verb first and prepositions last, find quiet errors as well as loud ones.
- After every fix the sentence goes back to the first check, because one fix can disturb another.
- The answer to a correction question is the smallest change that makes the sentence right; a longer rewrite tends to bring a new error or a new meaning.
Terms in this lesson
- dangling modifier
- An opening phrase, such as 'Walking into the hall', whose understood subject is not the subject of the main clause, so the sentence says the wrong thing did the action.
- error spotting
- A question that gives a sentence, usually in marked parts, and asks which part holds a grammatical error, or whether it has none. NMAT names it Error Identification.
- parallel structure
- Using the same grammatical form for the items of a list or a pair: three -ing forms, three infinitives or three nouns, not a mixture.
- subject–verb agreement
- The rule that a verb takes the person and number of its subject: 'The list of documents is printed', because the subject is 'list', not the noun beside the verb.
References
- About the NMAT exam (Graduate Management Admission Council (GMAC))
- XAT 2026: a quick overview (XLRI – Xavier School of Management)
- Important instructions, XAT 2026 (XLRI – Xavier School of Management)
- SNAP 2026 Bulletin (Symbiosis International (Deemed University))
- CMAT 2026 Information Bulletin (National Testing Agency (NTA))
- MAT FAQ (All India Management Association (AIMA))
- CAT 2026 FAQs (Indian Institutes of Management (CAT 2026, conducted by IIM Indore))
- Subject–verb agreement (English Grammar Today) (Cambridge University Press & Assessment)
- Neither, neither … nor and not … either (English Grammar Today) (Cambridge University Press & Assessment)
- Past simple or present perfect? (English Grammar Today) (Cambridge University Press & Assessment)
- Clauses: finite and non-finite (English Grammar Today) (Cambridge University Press & Assessment)
- Parallel structure (Purdue University Online Writing Lab)
- me (pronoun), Oxford Advanced Learner's Dictionary (Oxford University Press)
- discuss (verb), Oxford Advanced Learner's Dictionary (Oxford University Press)
- each (grammar point: each and every), Oxford Advanced Learner's Dictionary (Oxford University Press)
- number (noun): a plural verb after "a number of", Oxford Advanced Learner's Dictionary (Oxford University Press)
- cope (verb), Oxford Advanced Learner's Dictionary (Oxford University Press)
- return (verb), Oxford Advanced Learner's Dictionary (Oxford University Press)
- emphasize (verb), Oxford Advanced Learner's Dictionary (Oxford University Press)
- superior (adjective), Oxford Advanced Learner's Dictionary (Oxford University Press)
- succeed (verb), Oxford Advanced Learner's Dictionary (Oxford University Press)
- insist (verb), Oxford Advanced Learner's Dictionary (Oxford University Press)
- prefer (verb), Oxford Advanced Learner's Dictionary (Oxford University Press)
- agree (verb), Oxford Advanced Learner's Dictionary (Oxford University Press)
- married (adjective), Oxford Advanced Learner's Dictionary (Oxford University Press)
- consist of (phrasal verb), Oxford Advanced Learner's Dictionary (Oxford University Press)
- capable (adjective), Oxford Advanced Learner's Dictionary (Oxford University Press)
- interested (adjective), Oxford Advanced Learner's Dictionary (Oxford University Press)
- depend (verb), Oxford Advanced Learner's Dictionary (Oxford University Press)
- accuse (verb), Oxford Advanced Learner's Dictionary (Oxford University Press)
- difflib: helpers for computing deltas (Python Software Foundation)
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