True experimental research design
Duration: 2 min
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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 research design, beginning with an explanation of true experimental research designs, which are defined by the random assignment of subjects to experimental and control groups to ensure group equivalence at the start of the experiment. This method strengthens causal inferences. The lecture then details three specific types of true experimental designs: the Pretest-Post Test Design, where both groups are pretested and posttested after treatment; the Post-test-Only Control Group Design, where only the posttest is conducted after treatment; and the Solomon Four-Group Design, which combines elements of the other two to control for the effects of pretesting. The second part of the video transitions to quasi-experimental research designs, which are used when random assignment is not possible, and introduces the factorial research design, a method for studying the effects of two or more independent variables on a dependent variable, illustrated with an example involving study method and caffeine consumption.
Chapters
0:00 – 2:00 00:00-02:00
The video begins with a slide titled 'True Experimental Research Design'. The text explains that these designs are characterized by the random assignment of subjects to different groups, ensuring that the groups are equivalent at the start of the experiment, which helps establish stronger causal relationships. The slide then lists three types of true experimental test designs. The first is the 'Pretest-Post Test Design', where subjects are randomly assigned to experimental or control groups, both groups are pretested, the experimental group receives treatment, and then both groups take a post-test. The second is the 'Post-test-Only Control Group Design', where subjects are randomly assigned, the experimental group receives treatment, the control group does not, and only a post-test is conducted after the treatment. The third is the 'Solomon Four-Group Design', which combines elements of the other two designs, involving four groups to control for the effects of pretesting. The on-screen text is the primary source of information, with a small video of the instructor visible in the top right corner.
2:00 – 2:17 02:00-02:17
The video transitions to a new slide titled 'Quasi-Experimental Research Design'. The text defines this design as one where researchers manipulate an independent variable (IV) to observe its effects on a dependent variable (DV), but participants are not randomly assigned to groups, often using pre-existing groups. A flowchart diagram is displayed, showing the classification of research designs into 'True Experimental Design' and 'Quasi-Experimental Design', with the latter branching into 'One-Shot Case Study', 'One-Group Pretest-Posttest', 'Posttest-Only Control Group', and 'Factorial Design'. The slide then introduces the 'Factorial Research Design', defining it as a method to study the effects of two or more independent variables (IVs) on a dependent variable (DV). An example is provided: investigating the effects of study method (lecture vs. demonstration) and caffeine consumption (with vs. without caffeine) on memory performance. The on-screen text and diagram are the main sources of information.
The lecture progresses from the foundational concept of true experimental design, emphasizing random assignment for causal validity, to a detailed breakdown of its three main types. It then transitions to quasi-experimental designs, which are necessary when random assignment is not feasible, and concludes with the factorial design, a powerful method for examining the interaction of multiple variables. The progression moves from simple, controlled designs to more complex, real-world applicable ones, highlighting the importance of design choice in establishing valid research conclusions.