Short Trick to find total outcomes in an experiment

Duration: 12 min

This video lesson is available to enrolled students.

Inside: a video lesson and guided study material.

Module outline

Quantitative Ability: Percentage, Profit and Loss, Ratio and Proportion (Ratios), Average, Time and Work, Speed Time and Distance, Simple Interest and Compound Interest, Age Problems, Number System, Divisibility Rules, HCF LCM, Algebra, Permutation and Combination, Probability, Data Interpretation, Logarithm, Sequence and Series (Series), Powers and Exponents (Surds and Indices), Speed Mathematics and Basic Mathematics
Logical Reasoning: Seating Arrangements, Puzzle Solving (Puzzles), Data Arrangement, Coding Decoding, Blood Relations, Directions (Direction Test), Ranking, Order and Sequence, Data Sufficiency, Venn Diagram, Inequality, Series (Number and Letter Series) (Numerical Relations and Reasoning), Logical Sequence Of Words, Deductive and Inductive Reasoning (Logical Deduction and Induction) (Prepositional Reasoning), Selection Decision Table (Decision Making), Analogy, Non Verbal Reasoning (Spatial Aptitude) (Spatial Reasoning) (Visual Reasoning)
Verbal Ability: Comprehension / Reading Comprehension / Unseen Passages (Critical Reasoning) (Paragraph Questions), Subject Verb Agreement (Verb Noun Agreement), Tenses, Articles, Preposition, Conjunction, Modals, Active Passive Voice (Voice), Direct and Indirect Speech, Vocabulary, Sentence Re-arrangements (Para Jumbles) (Narrative Sequencing), Sentence Completion (Fill in the blanks), Sentence Correction (Error Correction), Cloze Test (Cloze Passage), Facts, Inference and Judgements
Programming Fundamentals (Technical): C Fundamentals
Data Structures (Technical): Introduction to DS, Array, Stack, Queue, Linked List, Tree, Graphs, Hashing
Algorithms (Technical): Algorithm Analysis, Sorting Algorithms, Greedy Algorithms, Dynamic Programming, Minimum Spanning Trees, Shortest Path Algos, Time Complexity Analysis, Advanced Algorithms
OOPs (Technical): Object Oriented Programming (OOPS)
DBMS (Technical): Basics of DBMS, ER Diagram, Relational Model & Functional Dependencies, Keys & Integrity Constraints, Normalization (1NF - BCNF), Decomposition Properties & 4NF, File Organization & Indexing, Relational Algebra, Relational Calculus, Transaction Management, Concurrency Control, Database Recovery, ORDBMS, Database Security & Authorization, Query Processing & Optimization, Enhanced Data Models, Data Warehousing & Mining, Big Data Systems, NoSQL
SQL (Technical): SQL
Operating Systems (Technical): Introduction to OS, Process Management, CPU Scheduling, Process Synchronization, Deadlock, Threads & Process Creation, Memory Management, Virtual Memory, Disc Scheduling, File Management, Windows OS, Linux OS, Security, Distributed Systems, Virtual Machines
Computer Networks (Technical): Introduction to CN, Data Communication, DLL: Access Control, DLL: Flow Control, DLL: Error Control, DLL: Framing, Data Link Layer - Ethernet, Net Layer: IPv4 & Proto, Net Layer: IP Addressing, Net Layer:Routing Protocol, Transport Layer Services, TL: Congestion & UDP, Application Layer, Hardware basics, Network Security, Mobile Technology, Cloud Computing and IoT, Cyber and Info Security
Software Engineering (Technical): Fundamentals of Software Engineering, Software Requirements and Quality Assurance, Software Design, Estimation and Metrics, Software Testing, Software Maintenance and Configuration Management
Coding/Automata Round: Coding Questions by Yash Sir, C Programming by Yash Sir, Programming in C++, Java, Python for Placements by Yash Sir, Pseudo Codes
Personality / Behavioral Assessment: Behavioral Assessment (Behavioral Competency Profiling) (Psychometric Test)
Writing Assessment: English Writing Ability

AI summary & chapters

AI Summary

An AI-generated summary of this video lecture.

This educational video, presented by Yash Jain from Knowledge Gate, is a lecture on the fundamental concept of probability, specifically focusing on calculating total outcomes in experiments. The video begins with an introduction to the topic, followed by a series of worked examples. The first example asks for the total outcomes when three coins are tossed, which is solved by listing all possible combinations (HHH, HHT, HTH, HTT, THH, THT, TTH, TTT) to arrive at 8 total outcomes. The second example calculates the total outcomes when a die is rolled four times, using the formula m^n where m is the number of outcomes per roll (6) and n is the number of rolls (4), resulting in 6^4 = 1296. The video concludes by presenting a general formula for such problems: if an experiment has 'm' total outcomes and is repeated 'n' times, the total number of outcomes is m^n. The instructor uses a digital whiteboard to write out the problems and solutions, and the video includes a copyright notice from Knowledge Gate Eduventures.

Chapters

0:00 – 2:00 00:00-02:00
The video opens with a title slide featuring the word "PROBABILITY" in a purple box, surrounded by four images: a dice on a green table, a basket of fruit, a pizza, and a business meeting. This transitions to a presentation slide with a pink background and a word cloud related to business and risk. The title "PROBABILITY" is at the top, and the instructor, Yash Jain, is visible in a small window. The slide also includes the text "- BY YASH JAIN" and a copyright notice at the bottom. The instructor begins the lecture, introducing the topic of probability.
2:00 – 5:00 02:00-05:00
The video displays a new slide with a yellow background and the text "Let's Play With Some Questions Now". The instructor then presents the first question: "Find the total outcomes when 3 coins are tossed together?". He begins to solve this by writing out the possible outcomes on a digital whiteboard, starting with H H H and then systematically listing all combinations of Heads (H) and Tails (T) for three coins, such as H H T, H T H, H T T, T H H, T H T, T T H, and T T T. He is explaining the process of finding the total number of possible results.
5:00 – 10:00 05:00-10:00
The instructor continues to list the outcomes for the three-coin toss problem, completing the list of 8 possible combinations. He then transitions to the second question: "Find the total outcomes when a dice is rolled 4 times?". He explains that a die has 6 faces, so there are 6 possible outcomes for a single roll. He then applies the formula for repeated experiments, writing 6 * 6 * 6 * 6 and calculating it as 6^4, which equals 1296. He also shows the calculation 1296 = 16 * 81. The instructor uses a digital whiteboard to write out the equations and calculations.
10:00 – 11:56 10:00-11:56
The video presents a slide titled "Yash Sir Special Short Trick". The instructor explains the general formula for calculating total outcomes when an experiment is repeated multiple times. He writes the formula: "Total outcomes when an experiment is done = m" and "Total outcomes if this experiment is repeated 'n' times = m^n". He uses the previous examples to illustrate this: for the coin toss, m=2 (H or T) and n=3, so 2^3 = 8. For the dice roll, m=6 and n=4, so 6^4 = 1296. The video ends with a final slide that says "THANKS FOR WATCHING".

The video provides a clear, step-by-step tutorial on calculating total outcomes in probability experiments. It starts with a conceptual introduction and then moves to practical examples. The first example, tossing three coins, is solved by exhaustive listing, which is a fundamental method. The second example, rolling a die four times, introduces the multiplicative principle, which is then generalized into a powerful formula (m^n). The instructor effectively uses a digital whiteboard to demonstrate the calculations, making the process easy to follow. The lesson progresses from a specific, manual method to a general, efficient formula, providing students with both a foundational understanding and a practical tool for solving similar problems.