Deloitte Online Test Pattern & Syllabus: Complete Guide to Success

Deloitte Online Test Pattern & Syllabus: Complete Guide to Success

Deloitte Online Test Pattern & Syllabus

If you’re preparing for Deloitte’s recruitment process, you’re likely aware of the importance of the Deloitte Online Test. This test is a crucial part of Deloitte’s hiring process, and understanding its structure and syllabus is the first step to success. In this guide, we’ll take you through the latest Deloitte Test Pattern, important topics for each section, and helpful preparation tips to ensure you perform at your best.

Deloitte Online Test Structure

The Deloitte Online Test is conducted on the AMCAT platform, a widely used online assessment platform for hiring. The test evaluates your aptitude, reasoning abilities, and verbal skills, with a focus on problem-solving and logical thinking.

Deloitte Online Test Pattern Overview

  • Total Questions: 50
  • Time Limit: 52 minutes
  • No Negative Marking
  • Sections:
    1. Quantitative Aptitude
    2. Logical Reasoning
    3. Verbal Ability

1. Deloitte Quantitative Aptitude Section

The Quantitative Aptitude section tests your mathematical skills and understanding of basic numerical concepts. With 14 questions and 20 minutes to answer them, it’s crucial to manage your time efficiently.

Key Topics for Quantitative Aptitude

  • Number Systems
  • Averages
  • Percentage
  • Simple Interest & Compound Interest
  • Time, Speed & Distance
  • Geometry
  • Coordinate Geometry
  • Logarithms
  • Quadratic Equations
  • Probability
  • Permutation & Combination
  • Time and Work

Preparation Tips for Quantitative Aptitude

  • Practice regularly with mock tests to improve speed and accuracy.
  • Focus on problem-solving strategies and basic arithmetic operations.
  • Spend extra time on Time and Work, Geometry, and Probability, as they are commonly featured.
Cut-off: 70% (Aim to attempt at least 10-12 questions)

2. Deloitte Logical Reasoning Section

This section evaluates your logical thinking, analytical skills, and problem-solving abilities. With 14 questions and 14 minutes allotted, time management is key.

1. Puzzles

Example: 5 friends are sitting in a row facing the north. They like different colors: Red, Blue, Green, Yellow, and White. From the given clues, can you determine who likes which color?Clues:
  1. A is sitting at one of the ends and does not like Red.
  2. C is sitting immediately next to the person who likes Red.
  3. The person who likes Yellow is sitting immediately to the right of B.
  4. E is sitting next to the person who likes Blue.
Answer: A likes White, B likes Green, C likes Red, D likes Yellow, and E likes Blue.

2. Seating Arrangements

Example: 8 people are sitting in a circle, facing the center. If P is sitting immediately to the left of Q, and T is sitting 3 places to the right of P, who is sitting opposite to P?Answer: After considering the positions and applying the clues, you can figure out the seating arrangement. The person sitting opposite to P would be M.

3. Data Sufficiency

Example: Does the person sitting at the 5th position from the left in a row of 10 people have a black shirt?Statement 1: The person sitting at the 5th position is wearing a shirt that is not blue or red. Statement 2: The shirt color of the person at the 5th position is not mentioned in the statements.Answer: The answer is No, as Statement 1 does not provide enough information about the specific shirt color. Statement 2 confirms that the color is not identified, so the answer is “Insufficient”.

4. Syllogisms

Example: All dogs are animals. All animals are mammals. Therefore, all dogs are mammals. Is the conclusion true?Answer: Yes, the conclusion is True, because if all dogs are animals and all animals are mammals, then logically all dogs are mammals.

5. Blood Relations

Example: A man’s mother is the grandmother of his son. What is the relationship between the man and his son?Answer: The man is the father of his son.

6. Pattern Recognition

Example: What comes next in the sequence: 2, 6, 12, 20, 30, ___?Answer: The difference between consecutive terms increases by 2: 6 – 2 = 4, 12 – 6 = 6, 20 – 12 = 8, 30 – 20 = 10. So, the next difference is 12. 30 + 12 = 42.

7. Logical Word Sequence

Example: Arrange the following words in a meaningful sequence:
  1. India
  2. Asia
  3. Earth
  4. Universe
  5. Solar System
Answer: The logical order should be: 3. Earth → 5. Solar System → 1. India → 2. Asia → 4. Universe. 

Preparation Tips for Logical Reasoning

  • Work on puzzles and seating arrangements, as these are common in this section.
  • Practice logical reasoning patterns to identify solutions faster.
  • Focus on time-efficient strategies to solve complex questions.
Cut-off: 70% (Aim to attempt 10-12 questions)

3. Deloitte Verbal Ability Section

Verbal AbilityThe Verbal Ability section assesses your English proficiency, including grammar, vocabulary, and reading comprehension. You’ll have 18 minutes to complete 22 questions, so manage your time wisely.

Key Topics for Verbal Ability

  • Synonyms & Antonyms
  • Sentence Correction & Improvement
  • Grammar
  • Vocabulary
  • Reading Comprehension
  • Error Identification
  • Tenses and Articles

Preparation Tips for Verbal Ability

  • Read regularly to improve your vocabulary and reading comprehension skills.
  • Focus on sentence improvement and grammar exercises.
  • Practice time-bound reading comprehension passages to increase speed.
Cut-off: 75% (Aim to attempt 16-18 questions)

4. Deloitte Computer Programming Section 

The Computer Programming section is for off-campus candidates and evaluates your programming skills, including data structures and object-oriented programming (OOP) concepts. This section is designed to assess your coding capabilities and understanding of basic programming concepts.

Key Topics for Computer Programming

  • 1. Data Types

    Example: Consider the following code in C++:
    int a = 5; float b = 3.14; char c = 'A';
    Explanation:
    • int is a data type that represents integer values.
    • float is a data type used for floating-point numbers (i.e., numbers with decimals).
    • char is a data type used to store a single character.
    Question: What is the output of the expression a + b where a = 5 and b = 3.14?Answer: The result would be a float, and the output would be 8.14.  

    2. Iteration, Recursion, Decision Making

    Example: Iteration (For Loop):
    for i in range(1, 6): print(i)
    Explanation: This is an iterative approach using a for loop to print numbers from 1 to 5.Recursion:
    def factorial(n): if n == 0: return 1 else: return n * factorial(n - 1)
    Explanation: This is a recursive function to compute the factorial of a number.Decision Making:
    if x > 10: print("x is greater than 10") else: print("x is less than or equal to 10")

    3. Functions & Scope

    Example:
    def foo(): x = 10 # Local variable print(x)foo() # print(x) # This will raise an error because x is local to foo
    Explanation:
    • x is a local variable to the function foo.
    • The variable x is not accessible outside of foo due to its scope being local.

    4. Arrays, Linked Lists, Trees, Graphs

    Example: Array:
    arr = [1, 2, 3, 4, 5] print(arr[2]) # Outputs: 3
    Linked List:
    python
    class Node: def __init__(self, value): self.value = value self.next = Nonehead = Node(1) second = Node(2) head.next = second
    Binary Tree:
    class TreeNode: def __init__(self, value): self.value = value self.left = None self.right = None
    Graph:
    graph = { "A": ["B", "C"], "B": ["A", "D"], "C": ["A"], "D": ["B"] }

    5. Stacks & Queues

    Example: Stack:
    stack = [] stack.append(1) # Push stack.append(2) # Push print(stack.pop()) # Pop, Outputs: 2
    Queue:
    from collections import deque queue = deque() queue.append(1) # Enqueue queue.append(2) # Enqueue print(queue.popleft()) # Dequeue, Outputs: 1

    6. Hash Tables & Heaps

    Example: Hash Table (Dictionary in Python):
    hash_table = {"apple": 3, "banana": 5, "cherry": 2} print(hash_table["apple"]) # Outputs: 3
    Heap:
    import heapq heap = [] heapq.heappush(heap, 3) # Push heapq.heappush(heap, 1) # Push print(heapq.heappop(heap)) # Pop, Outputs: 1

    7. Searching & Sorting Algorithms

    Example: Linear Search:
    def linear_search(arr, target): for i in range(len(arr)): if arr[i] == target: return i return -1
    Binary Search (requires sorted array):
    def binary_search(arr, target): low, high = 0, len(arr) - 1 while low <= high: mid = (low + high) // 2 if arr[mid] == target: return mid elif arr[mid] < target: low = mid + 1 else: high = mid - 1 return -1
    Bubble Sort:
    python
    def bubble_sort(arr): for i in range(len(arr)): for j in range(0, len(arr)-i-1): if arr[j] > arr[j+1]: arr[j], arr[j+1] = arr[j+1], arr[j]

    8. Polymorphism, Abstraction, Encapsulation

    Example: Polymorphism (Method Overriding):
    class Animal: def sound(self): print("Animal sound")class Dog(Animal): def sound(self): print(“Bark”)d = Dog() d.sound() # Outputs: Bark
    Abstraction:
    from abc import ABC, abstractmethodclass Shape(ABC): @abstractmethod def area(self): passclass Circle(Shape): def area(self): return 3.14 * 5 * 5c = Circle() print(c.area()) # Outputs: 78.5
    Encapsulation:
    class Person: def __init__(self, name, age): self.__name = name # Private attribute self.__age = age # Private attributedef get_name(self): return self.__namedef set_name(self, name): self.__name = namep = Person(“John”, 30) print(p.get_name()) # Outputs: John

    9. Complexity Theory (Big O Notation)

    Example:
    • O(1) Constant Time:
      def get_first_element(arr): return arr[0]
      The time complexity is O(1), because it always takes the same amount of time to retrieve the first element.
    • O(n) Linear Time:
      def print_elements(arr): for elem in arr: print(elem)
      The time complexity is O(n), where n is the number of elements in the array.
    • O(n^2) Quadratic Time (e.g., Bubble Sort):
      def bubble_sort(arr): for i in range(len(arr)): for j in range(len(arr)-i-1): if arr[j] > arr[j+1]: arr[j], arr[j+1] = arr[j+1], arr[j]
      The time complexity is O(n^2) because it contains two nested loops, each iterating over n elements.

Preparation Tips for Computer Programming

  • Strengthen your programming foundation by practicing data structures and algorithms.
  • Focus on writing clean, efficient code and optimizing your solutions.
  • Solve problems on platforms like LeetCode, HackerRank, or CodeForces to improve your coding skills.
Cut-off: 70% (Focus on mastering core programming concepts)

Conclusion: 

The Deloitte Online Test is a crucial step in the recruitment process, and preparation is the key to success. By practicing regularly, focusing on key topics, and managing your time efficiently during the test, you’ll increase your chances of clearing the exam and progressing to the next stages of the Deloitte recruitment process.Make sure to take mock tests, revise important topics, and stay calm during the exam. With the right preparation and mindset, you’re well on your way to acing the Deloitte Online Test.Click here to know more our program!Deloitte's recruitment process,