Products related to Reasoning:
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Abductive Reasoning in Science
In abductive reasoning, scientific theories are evaluated on the basis of how well they would explain the available evidence.There are a number of subtly different accounts of this type of reasoning, most of which are inspired by the popular slogan 'Inference to the Best Explanation.' However, these accounts disagree about exactly how to spell out the slogan so as to avoid various problems for abductive reasoning.This Element aims, firstly, to give an opinionated overview both of the many accounts of abductive reasoning that have been proposed and the problems that have motivated them; and, secondly, to critically evaluate these accounts in a way that points toward a systematic view of the nature and purpose of abductive reasoning in science.This title is also available as Open Access on Cambridge Core.
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Understanding Reasoning: Verbal Reasoning
The Understanding Reasoning series helps pupils to understand and answer correctly reasoning questions, as found in the 11+, 12+, 13+ and other school selection tests.The books provide concise explanations and examples of all the question types occurring in the 11+ together with practical workbook-style activities to consolidate learning.The step-by-step explanations are clear and include 'how to' instructions.Intensive practice enables pupils to gain confidence as they tackle each new question type.Correct answers are provided at the back of each book for quick and easy marking.Verbal reasoning activities use letters and words to explore pupils' understanding of language and meaning.Using methods that are quite distinct from traditional literacy activities, pupils' verbal skills are stretched to the full.Question types covered include the following: alphabet and word patterns, vocabulary, spelling, mathematical questions and problem solving.
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Understanding Reasoning: Non-verbal Reasoning
The Understanding Reasoning series helps pupils to understand and answer correctly reasoning questions, as found in the 11+, 12+, 13+ and other school selection tests.The books provide concise explanations and examples of all the question types occurring in the 11+ together with practical workbook-style activities to consolidate learning.The step-by-step explanations are clear and include 'how to' instructions.Intensive practice enables pupils to gain confidence as they tackle each new question type.Correct answers are provided at the back of each book for quick and easy marking.Non-verbal reasoning activities may be used with all pupils, including those whose literacy skills are poor and those for whom English is a second language.Question types covered include the following: identifying shapes and patterns, missing shapes and patterns, rotating shapes/patterns, codes, logic and combined shapes.
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Reasoning, Judging, Deciding : The Science of Thinking
Are humans effective thinkers? How do we decide what is right? Can we avoid being duped by fake news?Thinking and Reasoning is the study of how humans think; exploring rationality, decision making and judgment within all contexts of life.With contemporary case studies and reflective questions to develop your understanding of key dilemmas, this book covers the fundamentals of the science behind thinking, reasoning, and decision-making, making it essential reading for any student of Thinking and Reasoning. From heuristic biases to the cognitive science of religion, and from artificial intelligence to conspiracy theories, Wastell & Howarth's text clearly and comprehensibly introduces you to the core theories of thinking, leaving no stone unturned, before showing you how to apply theory to practice. 'The unique selling point of the book is the inclusion of current topics and recent developments, a very good structure and it approaches the field from a very wide angle.'
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What is spatial reasoning?
Spatial reasoning is the ability to understand and manipulate visual information about objects and their relationships in space. It involves skills such as mental rotation, visualization, and understanding of spatial patterns. People with strong spatial reasoning skills can easily interpret and create visual representations, understand maps and diagrams, and solve problems involving spatial relationships. This ability is important in fields such as mathematics, engineering, architecture, and design.
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What is logical reasoning?
Logical reasoning is the process of using rational thinking and evidence to come to a conclusion or make a decision. It involves analyzing information, identifying patterns, and drawing valid inferences based on the available facts. Logical reasoning helps individuals to think critically, solve problems, and make sound judgments by following a systematic and coherent thought process. It is an essential skill in various fields such as mathematics, science, philosophy, and everyday decision-making.
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Don't you understand inductive reasoning?
Inductive reasoning is a method of reasoning that involves making generalizations based on specific observations or evidence. It is different from deductive reasoning, which involves drawing specific conclusions from general principles. Inductive reasoning is often used in scientific research and everyday decision-making to make educated guesses or predictions based on patterns or trends. It is important to understand inductive reasoning in order to make informed judgments and draw logical conclusions from the information available.
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What is logical reasoning ability?
Logical reasoning ability refers to the capacity to think critically, analyze information, and draw valid conclusions based on evidence and facts. It involves the ability to identify patterns, make connections between ideas, and solve problems systematically. Individuals with strong logical reasoning skills can evaluate arguments, make sound decisions, and navigate complex situations effectively. This ability is essential in various aspects of life, including academics, professional settings, and everyday problem-solving.
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Statistical Foundations, Reasoning and Inference : For Science and Data Science
This textbook provides a comprehensive introduction to statistical principles, concepts and methods that are essential in modern statistics and data science.The topics covered include likelihood-based inference, Bayesian statistics, regression, statistical tests and the quantification of uncertainty.Moreover, the book addresses statistical ideas that are useful in modern data analytics, including bootstrapping, modeling of multivariate distributions, missing data analysis, causality as well as principles of experimental design.The textbook includes sufficient material for a two-semester course and is intended for master’s students in data science, statistics and computer science with a rudimentary grasp of probability theory.It will also be useful for data science practitioners who want to strengthen their statistics skills.
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Making Sense of Numbers : Quantitative Reasoning for Social Research
Making Sense of Numbers teaches students the skills they need to be both consumers and producers of quantitative research: able to read about, collect, calculate, and communicate numeric information for both everyday tasks and school or work assignments.The text teaches how to avoid making common errors of reasoning, calculation, or interpretation by introducing a systematic approach to working with numbers, showing students how to figure out what a particular number means.The text also demonstrates why it is important to apply a healthy dose of skepticism to the numbers we all encounter, so that we can understand how those numbers can (and cannot) be interpreted in their real-world context.Jane E. Miller uses annotated examples on a wide variety of topics to illustrate how to use new terms, concepts, and approaches to working with numbers.End-of-chapter engagement activities designed based on Miller’s three decades of teaching experience can be used in class or as homework assignments, with some for students to do individually and others intended for group discussion.The book is ideally suited for a range of courses, including quantitative reasoning, research methods, basic statistics, data analysis, and communicating quantitative information. An instructor website for the book includes a test bank, editable PowerPoint slides, and tables and figures from the book.
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Logic in Computer Science : Modelling and Reasoning about Systems
Recent years have seen the development of powerful tools for verifying hardware and software systems, as companies worldwide realise the need for improved means of validating their products.There is increasing demand for training in basic methods in formal reasoning so that students can gain proficiency in logic-based verification methods.The second edition of this successful textbook addresses both those requirements, by continuing to provide a clear introduction to formal reasoning which is both relevant to the needs of modern computer science and rigorous enough for practical application.Improvements to the first edition have been made throughout, with extra and expanded sections on SAT solvers, existential/universal second-order logic, micro-models, programming by contract and total correctness.The coverage of model-checking has been substantially updated.Further exercises have been added. Internet support for the book includes worked solutions for all exercises for teachers, and model solutions to some exercises for students.
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Human Reasoning
This Element is on new developments in the psychology of reasoning that raise or address philosophical questions.In traditional studies in the psychology of reasoning, the focus was on inference from arbitrary assumptions and not at all from beliefs, and classical binary logic was presupposed as the only standard for human reasoning.But recently a new Bayesian paradigm has emerged in the discipline.This views ordinary human reasoning as mostly inferring probabilistic conclusions from degrees of beliefs, or from hypothetical premises relevant to a purpose at hand, and as often about revising or updating degrees of belief.This Element also covers new formulations of dual-process theories of the mind, stating that there are two types of mental processing, one rapid and intuitive and shared with other animals, and the other slow and reflective and more characteristic of human beings.The final topic covered is the new developments and rationality.
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What is the reasoning behind the favorite subjects of Political Science and History?
Political Science and History are popular subjects because they provide a deep understanding of how societies, governments, and cultures have evolved over time. Political Science allows students to analyze political systems, policies, and international relations, while History offers insights into past events, their causes, and their impact on the present. Both subjects help students develop critical thinking, research, and analytical skills that are valuable in a wide range of careers, including government, law, journalism, and academia.
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Would Kant agree with the reasoning?
Kant would likely not agree with the reasoning presented in the text. Kant's ethical philosophy is based on the idea of universal moral principles that apply to all rational beings, regardless of the consequences. The reasoning in the text seems to be based on the idea of achieving a desired outcome, which goes against Kant's deontological ethics. Kant would argue that the morality of an action is determined by whether it can be willed as a universal law, not by the potential benefits or consequences.
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Do Muslims have better spatial reasoning skills?
There is no scientific evidence to suggest that Muslims have inherently better spatial reasoning skills compared to individuals of other faiths or backgrounds. Spatial reasoning skills are developed through a combination of genetics, environment, education, and practice, rather than being determined by religious affiliation. It is important to avoid making generalizations or assumptions about a group of people based on their religion.
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What does the term "circular reasoning" mean?
Circular reasoning refers to a logical fallacy in which the conclusion of an argument is assumed in one of the premises. Essentially, the argument goes in a circle, with the conclusion being used to support the premise, which in turn supports the conclusion. This type of reasoning is invalid because it does not provide any new information or evidence to support the conclusion, leading to a self-reinforcing loop of logic.
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