Скачать или смотреть #3 - Probability | IT Placement | Aptitude |

Basic Probability Formulas
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i) Probability Range – 0 ≤ P(A) ≤ 1
ii) Rule of Complementary Events – P(A') + P(A) =1
iii) Rule of Addition – P(A∪B) = P(A) + P(B) – P(A∩B)
iv) Disjoint Events – Events A and B are disjoint if P(A∩B) = 0
v) Conditional Probability – P(A | B) = 𝑃(𝐴∩𝐵)/𝑃(𝐵)
vi) Bayes Formula – P(A | B) = [𝑃(𝐵∣𝐴).𝑃(𝐴)]/𝑃(𝐵)
vii) Independent Events – Events A and B are independent if. P(A∩B) = P(A) ⋅ P(B).

From an IT placement preparation point of view, mastering probability and statistics is crucial. These topics are foundational for many technical roles, including data science, machine learning, and software engineering. Aptitude exams often feature problems based on probability and statistics to assess a candidate's ability to analyze data, interpret results, and make data-driven decisions. A strong grasp of these concepts demonstrates analytical thinking and problem-solving skills, which are highly valued in the IT industry. Preparing thoroughly in these areas can significantly enhance a candidate's performance in aptitude tests and technical interviews, thereby improving their chances of securing a desirable IT position.

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