We at CareerPower have compiled all CAT Previous Year Question Papers from CAT 2017 to CAT 2024, complete with accurate answers and full video solutions for every question. These papers are structured slot-wise and section-wise, covering VARC, DILR, and Quant individually. Preparing for the CAT exam requires smart planning, consistent practice, and familiarity with real exam standards. One of the most powerful tools for aspirants is solving the CAT Exam Previous Year Question Papers (PYQs). These papers offer authentic exposure to exam patterns, types of questions, difficulty levels, and time-management challenges.

CAT Exam Previous Year Question Papers

CAT Previous Year Question Papers (PYQs) are actual question sets from previous CAT examinations that help aspirants understand the real exam pattern, difficulty level, and topic distribution. Practicing these papers boosts accuracy, time management, and confidence. They offer valuable insight into commonly asked question types across VARC, DILR, and QA sections. Solving PYQs under timed conditions also helps develop exam temperament and reduces stress on the actual test day. For effective preparation, students should regularly analyze mistakes from these papers and focus on improving weaker areas through consistent practice and revision.

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CAT Exam Previous Year Question Papers PDF

CAT Exam Previous Year Question Papers are valuable resources for understanding real exam trends and difficulty levels. Aspirants can download these PYQs in PDF format to practice consistently, improve accuracy, and build confidence for the actual exam.

CAT Exam (PYQ)Download PDF
CAT 2024 Official Paper (Held On_ 24 Nov, 2024 Slot 1)Click Here
CAT 2024 Official Paper (Held On_ 24 Nov, 2024 Slot 2)Click Here
CAT 2024 Official Paper (Held On_ 24 Nov, 2024 Slot 3)Click Here
CAT_2023_Official_Paper_Held_On_26_Nov,_2023_Shift_1Click Here
CAT_2023_Official_Paper_Held_On_26_Nov,_2023_Shift_2Click Here
CAT_2023_Official_Paper_Held_On_26_Nov,_2023_Shift_3Click Here
CAT_27_Nov_2022_Slot_1_Official_Paper_EnglishClick Here
CAT_27_Nov_2022_Slot_3_Official_Paper_EnglishClick Here
CAT_2021_Slot_2_Question Paper (English)Click Here
CAT_2021_Slot_3_Question Paper (English)Click Here
CAT_2020_Slot_1 Question Paper_(English)Click Here
CAT_2020_Slot_3_Question Paper_(English)Click Here
CAT_2019_Slot_1_Question Paper_(English)Click Here
CAT_2019_Slot_2_Question Paper_(English)Click Here
CAT_2018_Slot_1_English_Question Paper_(English)Click Here
CAT_2018_Slot_2_Question Paper_(English)Click Here
CAT_2017_Slot_1_Question Paper_(English)Click Here
CAT_2017_Slot_2_English_Question Paper_(English)Click Here

What Are CAT Exam PYQs?

CAT PYQs are official question papers from past exam years. They are used to:

  • Understand how the exam was structured in previous years
  • Evaluate changes in pattern or difficulty level
  • Practice authentic questions directly asked in the past

These papers are usually available year-wise and slot-wise (Slot-1, Slot-2 etc.).

Section-Wise Focus Areas For CAT Exam Previous Year Question Papers

Verbal Ability & Reading Comprehension

  • RC passages from humanities, ecology, psychology, economy
  • Para-jumbles / Para completion
  • Odd sentence out
  • Critical reasoning skills

Data Interpretation & Logical Reasoning

  • Puzzle-based sets
  • Seating arrangements
  • Mathematical logic
  • Caselets with integrated data points
  • Charts, bar graphs, line graphs

Quantitative Ability

  • Arithmetic (percentages, averages, ratios, profit-loss)
  • Algebra (equations, functions, inequalities)
  • Geometry & Mensuration (triangles, circles, 3D shapes)
  • Number System (factors, divisibility)
  • Modern Math (probability, permutation-combination, set theory)
FAQs

olving CAT previous year question papers helps you understand the exam pattern, question difficulty, and topic weightage. It also improves speed, accuracy, and time management, which are crucial for the actual exam.

Ideally, practice at least 5–7 years of CAT papers. The pattern remains similar, so this range helps you analyze trend variations and recurring topics in VARC, DILR, and QA sections.

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