Quasi - Experimental Research Design

Duration: 1 min

This video lesson is available to enrolled students.

Inside: a video lesson and guided study material.

Module outline

Paper-I | Mathematical Abilities: Ratio and Proportion (Ratios), Divisibility Rules, Data Interpretation, Mixture and Alligation, Number System, Speed Time and Distance, Arithmetic, Percentage, Average, Simple Interest and Compound Interest, Profit and Loss, Partnership, Time and Work, Algebra, Mensuration and Geometry, Trigonometry, Linear Algebra
Paper-I | Reasoning & General Intelligence: Series (Number and Letter Series) (Numerical Relations and Reasoning), Coding Decoding, Data Sufficiency, Non Verbal Reasoning (Spatial Aptitude) (Spatial Reasoning) (Visual Reasoning), Syllogisms, Deductive and Inductive Reasoning (Logical Deduction and Induction) (Prepositional Reasoning), Seating Arrangements, Blood Relations, Directions (Direction Test), Analytical Reasoning (Counting Figures Reasoning), Puzzle Solving (Puzzles), Calendar, Clock, Cubes & Dices, Selection Decision Table (Decision Making), Logical Sequence Of Words, Crypt Arithmetic, Venn Diagram, Data Arrangement, Inequality, Analogy, Ranking, Order and Sequence, Clerical Aptitude, Verbal Classification
Paper-I | English Language & Comprehension: Vocabulary, Noun, Subject Verb Agreement (Verb Noun Agreement), Adjectives, Tenses, Pronoun, Preposition, Articles, Direct and Indirect Speech, Conjunction, Modals, Sentence Re-arrangements (Para Jumbles) (Narrative Sequencing), Sentence Correction (Error Correction), Sentence Completion (Fill in the blanks), Comprehension / Reading Comprehension / Unseen Passages (Critical Reasoning) (Paragraph Questions), Cloze Test (Cloze Passage), Verbal Analogy (Word Based Analogy), Sentence Construction, Active Passive Voice (Voice), Determiner, Facts, Inference and Judgements
Paper-I | General Awareness: Polity, Physics, Biology, Chemistry, Environment, GK- Current Affairs, Static General Knowledge, History, Geography, Indian Economy
Paper-I | Computer Knowledge/Proficiency): Basics of COA, Transport Layer Services, Keyboard Shortcuts, MS Office Applications, MS Office by Yash Sir, Emerging Tech Trends, Society, Law & Ethics, Website, Browser & Services, Internet Fundamentals, Web Design & Development, Introduction to CN, Hardware basics, Network Security, Application Layer, Cyber and Info Security, Cyber Threats and Malware Attacks, Cyber Safety and Security, Role of Internet and Web Services, Security in Mobile and Wireless Computing
Paper-II | Statistics: Statistics, Probability, Research Process Steps

AI summary & chapters

AI Summary

An AI-generated summary of this video lecture.

The video presents a lecture on two types of research designs: Quasi-Experimental and Factorial. It begins by defining a Quasi-Experimental Research Design as a method where researchers manipulate an Independent Variable (IV) to observe its effects on a Dependent Variable (DV), but unlike true experiments, participants are not randomly assigned to groups. This design often uses pre-existing groups or naturally occurring conditions. The lecture then transitions to the Factorial Research Design, which is defined as a method used to study the effects of two or more Independent Variables (IVs) on a Dependent Variable (DV). The key feature is that researchers manipulate and combine different levels of each IV to examine both individual and combined effects. An example provided is investigating the effects of study method (lecture vs. demonstration) and caffeine consumption (with vs. without) on memory performance. A flowchart on the right side of the screen visually organizes these concepts, showing the hierarchy from Experimental Research Design down to specific types like Pre-Experimental, Quasi-Experimental, and Factorial designs.

Chapters

0:00 – 1:01 00:00-01:01
The video displays a slide with the title 'Quasi-Experimental Research Design'. The text explains that in this design, researchers manipulate an IV to observe its effects on a DV, similar to experimental designs, but often use pre-existing groups or naturally occurring conditions because participants are not randomly assigned. The slide then introduces 'Factorial Research Design', defining it as a method to study the effects of two or more Independent Variables (IVs) on a Dependent Variable (DV). The text states that researchers manipulate and combine different levels of each IV to examine their individual and combined effects. An example is given: investigating the effects of study method (lecture vs. demonstration) and caffeine consumption (with caffeine vs. without caffeine) on memory performance. A flowchart on the right side of the screen shows a hierarchical structure of research designs, starting with 'Experimental Research Design' and branching into 'Pre-Experimental', 'True Experimental', 'Quasi-Experimental', and 'Statistical Design', with 'Factorial Design' being a sub-type of 'Quasi-Experimental Design'.

The lecture systematically introduces two key research design methodologies. It first establishes the Quasi-Experimental design as a practical alternative to true experiments, highlighting its core feature of non-random assignment. It then builds upon this by introducing the Factorial design, which is a powerful method for investigating complex interactions between multiple variables. The visual flowchart effectively contextualizes these designs within the broader framework of experimental research, showing how factorial designs are a specific type of quasi-experimental approach used to study the combined effects of multiple independent variables.