수학

수학은 시장 행동에서 자연 현상에 이르기까지 모든 것에 대한 우리의 이해를 형성하며, 혼돈 속에 숨겨진 패턴과 복잡성 속의 실용적인 해결책을 드러냅니다. 이 책들은 우리 세계를 지배하는 숫자 뒤에 숨겨진 우아한 원리와 매혹적인 이야기를 조명하여, 수학적 개념을 일상생활에서 이해하기 쉽고 의미 있게 만들어 줍니다.

수학 도서 요약

PYTHON FOR DATA ANALYSIS

저자: Ryshith Doyle • 2019

The systematic NumPy and Pandas walkthrough: import, clean, combine, and analyze data in Python.

3.67

🐍 Python Programming 📊 Data Analysis 🧹 Data Wrangling 🧱 Data Structures 🔢 Numerical Computing

PYTHON FOR DATA ANALYSIS

The systematic NumPy and Pandas walkthrough: import, clean, combine, and analyze data in Python.

저자: Ryshith Doyle 2019 60 페이지

3.67

6 개의 평점

🐍 Python Programming 📊 Data Analysis 🧹 Data Wrangling 🧱 Data Structures 🔢 Numerical Computing

Visualizing Mathematics with 3D Printing

저자: Henry Segerman • 2016

3D printing turns polyhedra, knots, and 4D shadows into hands-on objects you finally grasp.

4.08

🖨️ 3d Printing 🧮 Mathematical Models 🌌 Higher Dimensions 🌀 Hyperbolic Geometry 🪢 Knot Theory

Visualizing Mathematics with 3D Printing

3D printing turns polyhedra, knots, and 4D shadows into hands-on objects you finally grasp.

저자: Henry Segerman 2016 200 페이지

4.08

13 개의 평점

🖨️ 3d Printing 🧮 Mathematical Models 🌌 Higher Dimensions 🌀 Hyperbolic Geometry 🪢 Knot Theory

The Midrange Theory

저자: Seth Partnow • 2021

Analytics was going to kill the eye test. It proved why eyes still matter.

4.09

500+

🏀 Basketball Analytics 💰 Sports Economics 📊 Data-Driven Decisions 📏 Advanced Metrics ⚾ Moneyball

The Midrange Theory

Analytics was going to kill the eye test. It proved why eyes still matter.

저자: Seth Partnow 2021 288 페이지

4.09

500+ 개의 평점

🏀 Basketball Analytics 💰 Sports Economics 📊 Data-Driven Decisions 📏 Advanced Metrics ⚾ Moneyball

Basketball on Paper

저자: Dean Oliver • 2003

Basketball's scoreboard is a liar. Here is what actually decides who wins and who loses.

4.06

467

🏀 Basketball Analytics 📊 Sports Analytics 📈 Performance Metrics 🔢 Statistical Modeling 📋 Data-Driven Coaching

Basketball on Paper

Basketball's scoreboard is a liar. Here is what actually decides who wins and who loses.

저자: Dean Oliver 2003 392 페이지

4.06

467 개의 평점

🏀 Basketball Analytics 📊 Sports Analytics 📈 Performance Metrics 🔢 Statistical Modeling 📋 Data-Driven Coaching

An Essay on the Psychology of Invention in the Mathematical Field

저자: Jacques Hadamard • 1945

Mathematical discovery relies on the unconscious, not logic; beauty picks the winning ideas.

3.97

221

🔢 Mathematical Creativity 🧠 Cognitive Psychology 🌊 Unconscious Processing 👁️ Visual Thinking ✨ Beauty In Mathematics

An Essay on the Psychology of Invention in the Mathematical Field

Mathematical discovery relies on the unconscious, not logic; beauty picks the winning ideas.

저자: Jacques Hadamard 1945 162 페이지

3.97

221 개의 평점

🔢 Mathematical Creativity 🧠 Cognitive Psychology 🌊 Unconscious Processing 👁️ Visual Thinking ✨ Beauty In Mathematics

Diversity and Complexity

저자: Scott E. Page • 2010

Diversity isn't a slogan: it's a measurable property with predictable benefits and knowable limits.

4.12

207

🌀 Complexity Science 🏜️ Santa Fe Institute 🐝 Emergence 🔄 Adaptive Systems 🛡️ System Resilience

Diversity and Complexity

Diversity isn't a slogan: it's a measurable property with predictable benefits and knowable limits.

저자: Scott E. Page 2010 304 페이지

4.12

207 개의 평점

🌀 Complexity Science 🏜️ Santa Fe Institute 🐝 Emergence 🔄 Adaptive Systems 🛡️ System Resilience

Why Study Mathematics?

저자: Vicky Neale • 2020

A math degree opens careers from kidney swaps to climate models. Effort trumps genius every time.

3.97

📐 Applied Mathematics 🧠 Growth Mindset 📊 Data Science ➗ Mathematical Thinking 📖 Popular Mathematics

Why Study Mathematics?

A math degree opens careers from kidney swaps to climate models. Effort trumps genius every time.

저자: Vicky Neale 2020 208 페이지

3.97

38 개의 평점

📐 Applied Mathematics 🧠 Growth Mindset 📊 Data Science ➗ Mathematical Thinking 📖 Popular Mathematics

Why Data Science Projects Fail

저자: Douglas Gray • 2024

Eighty percent of AI projects fail. The models work fine; the people, data, and expectations don't.

5.00

📊 Data Science Management 🤖 Ai Implementation ⚙️ Mlops 🧹 Data Quality 🔧 Data Engineering

Why Data Science Projects Fail

Eighty percent of AI projects fail. The models work fine; the people, data, and expectations don't.

저자: Douglas Gray 2024

5.00

19 개의 평점

📊 Data Science Management 🤖 Ai Implementation ⚙️ Mlops 🧹 Data Quality 🔧 Data Engineering

Credit Scoring and Its Applications

저자: Lyn C. Thomas • 1987

How the algorithms that decide who gets a loan actually work, and how to build them.

3.62

💳 Credit Risk 🏦 Consumer Lending 📊 Statistical Modeling 🔮 Predictive Analytics ⚙️ Operational Research

Credit Scoring and Its Applications

How the algorithms that decide who gets a loan actually work, and how to build them.

저자: Lyn C. Thomas 1987 260 페이지

3.62

13 개의 평점

💳 Credit Risk 🏦 Consumer Lending 📊 Statistical Modeling 🔮 Predictive Analytics ⚙️ Operational Research

Small Worlds

저자: Duncan J. Watts • 1999

A few distant links turn clustered networks into superhighways for disease, ideas, and synchrony.

3.88

🕸️ Network Science 📐 Graph Theory 🔗 Complex Systems 📊 Mathematical Modeling 🌊 Emergent Behavior

Small Worlds

A few distant links turn clustered networks into superhighways for disease, ideas, and synchrony.

저자: Duncan J. Watts 1999 280 페이지

3.88

85 개의 평점

🕸️ Network Science 📐 Graph Theory 🔗 Complex Systems 📊 Mathematical Modeling 🌊 Emergent Behavior

Senior Secondary School Mathematics For Class - 12

저자: R.S. Aggarwal • 2013

Ace Class 12 math: every topic, from relations to calculus, explained with clarity.

3.72

294

📐 Precalculus 📚 High School Math 🔺 Trigonometry 🧮 Matrices 📉 Differential Equations

Senior Secondary School Mathematics For Class - 12

Ace Class 12 math: every topic, from relations to calculus, explained with clarity.

저자: R.S. Aggarwal 2013

3.72

294 개의 평점

📐 Precalculus 📚 High School Math 🔺 Trigonometry 🧮 Matrices 📉 Differential Equations

Mastering Poker Math

저자: Charles W. Clayton • 2019

Forty percent of poker is math. Most players learn none of it. That edge is yours.

3.79

🃏 Poker Strategy ♠️ Texas Hold'em 🏆 Tournament Poker 🧮 Poker Mathematics 🎯 Game Theory

Mastering Poker Math

Forty percent of poker is math. Most players learn none of it. That edge is yours.

저자: Charles W. Clayton 2019 304 페이지

3.79

33 개의 평점

🃏 Poker Strategy ♠️ Texas Hold'em 🏆 Tournament Poker 🧮 Poker Mathematics 🎯 Game Theory

Using Graphic Novels in the STEM Classroom

저자: William Boerman-Cornell • 2023

How graphic novels make STEM concepts click, and which ones to use in your classroom.

5.00

🧪 Stem Education 📚 Comics In The Classroom 👁️ Visual Literacy 📖 Multimodal Literacy 🎓 Educational Comics

Using Graphic Novels in the STEM Classroom

How graphic novels make STEM concepts click, and which ones to use in your classroom.

저자: William Boerman-Cornell 2023 168 페이지

5.00

1 개의 평점

🧪 Stem Education 📚 Comics In The Classroom 👁️ Visual Literacy 📖 Multimodal Literacy 🎓 Educational Comics

The Last Man Who Knew Everything

저자: Mike Hockney • 2012

The universe is math, not matter, and your mind is a zero with infinite potential.

4.46

🌌 Mathematical Platonism 🧠 Panpsychism 🕯️ Esoteric Philosophy 🔄 Hegelian Dialectics 👁️ Secret Societies

The Last Man Who Knew Everything

The universe is math, not matter, and your mind is a zero with infinite potential.

저자: Mike Hockney 2012 298 페이지

4.46

90 개의 평점

🌌 Mathematical Platonism 🧠 Panpsychism 🕯️ Esoteric Philosophy 🔄 Hegelian Dialectics 👁️ Secret Societies

My Good Grief

저자: Cindyanne Kershaw • 2006

Seen enough options? There is a mathematically optimal moment to stop looking and commit.

4.50

💻 Applied Computer Science 🔬 Science-Based Self-Help 🤔 Rational Decision Making 📊 Bayesian Reasoning 🎲 Game Theory Applications

My Good Grief

Seen enough options? There is a mathematically optimal moment to stop looking and commit.

저자: Cindyanne Kershaw 2006

4.50

2 개의 평점

💻 Applied Computer Science 🔬 Science-Based Self-Help 🤔 Rational Decision Making 📊 Bayesian Reasoning 🎲 Game Theory Applications

Data Structures and Problem Solving Using Java

저자: Mark Allen Weiss • 2009

Coding tricks lose to growth rates. The data structures and guarantees that survive at scale.

3.58

🏗️ Data Structures 🧠 Algorithmic Thinking 🕸️ Graph Algorithms 🔄 Recursion 🧱 Object Oriented Design

Data Structures and Problem Solving Using Java

Coding tricks lose to growth rates. The data structures and guarantees that survive at scale.

저자: Mark Allen Weiss 2009 1032 페이지

3.58

36 개의 평점

🏗️ Data Structures 🧠 Algorithmic Thinking 🕸️ Graph Algorithms 🔄 Recursion 🧱 Object Oriented Design

AIQ

저자: Nick Polson • 2018

What a 19th-century nurse and a lost submarine reveal about the algorithms that now run your life.

4.15

500+

🤖 Ai Explainers 📊 History Of Statistics 🎲 Bayesian Thinking 🔮 Prediction And Forecasting 🤝 Human-Machine Collaboration

AIQ

What a 19th-century nurse and a lost submarine reveal about the algorithms that now run your life.

저자: Nick Polson 2018 288 페이지

4.15

500+ 개의 평점

🤖 Ai Explainers 📊 History Of Statistics 🎲 Bayesian Thinking 🔮 Prediction And Forecasting 🤝 Human-Machine Collaboration

So lügt man mit Statistik

저자: Walter Krämer • 1991

Precision, percentages, and pretty charts: a catalog of ways statistics are rigged to mislead you.

3.74

136

📊 Statistical Literacy 🎭 Data Manipulation 🧠 Cognitive Biases 🗞️ Media Criticism 📉 Misleading Charts

So lügt man mit Statistik

Precision, percentages, and pretty charts: a catalog of ways statistics are rigged to mislead you.

저자: Walter Krämer 1991 206 페이지

3.74

136 개의 평점

📊 Statistical Literacy 🎭 Data Manipulation 🧠 Cognitive Biases 🗞️ Media Criticism 📉 Misleading Charts

Az elvek csapodár természete

저자: Mérő László • 2008

Reason depends on emotion. Logic has limits. A psychologist's case for pragmatism over purity.

4.25

🧠 Cognitive Biases 🎯 Game Theory 🧬 Cultural Evolution 📚 History Of Science 🎭 Emotion And Reason

Az elvek csapodár természete

Reason depends on emotion. Logic has limits. A psychologist's case for pragmatism over purity.

저자: Mérő László 2008 230 페이지

4.25

61 개의 평점

🧠 Cognitive Biases 🎯 Game Theory 🧬 Cultural Evolution 📚 History Of Science 🎭 Emotion And Reason

Einstein's Fridge

저자: Paul Sen • 2021

The science of heat built the modern world and governs time's arrow, life, and black holes.

4.26

500+

📜 History Of Physics 🔥 Thermodynamics 🔬 History Of Science ⚡ Energy 🔀 Entropy

Einstein's Fridge

The science of heat built the modern world and governs time's arrow, life, and black holes.

저자: Paul Sen 2021 320 페이지

4.26

500+ 개의 평점

📜 History Of Physics 🔥 Thermodynamics 🔬 History Of Science ⚡ Energy 🔀 Entropy

Python for Data Analysis

저자: Oscar Scratch • 2019

Python data analysis, taught through questions: NumPy, Pandas, and the bridge to machine learning.

3.50

🧮 Scientific Computing 🔄 Data Manipulation 📊 Data Visualization 🐍 Introductory Programming 📈 Beginner Data Science

Python for Data Analysis

Python data analysis, taught through questions: NumPy, Pandas, and the bridge to machine learning.

저자: Oscar Scratch 2019 249 페이지

3.50

2 개의 평점

🧮 Scientific Computing 🔄 Data Manipulation 📊 Data Visualization 🐍 Introductory Programming 📈 Beginner Data Science

Hands-On Quantum Information Processing with Python

저자: Dr. Makhamisa Senekane • 2021

Python for quantum computing: from qubits to algorithms, cryptography, and machine learning.

4.00

⚛️ Quantum Computing 💻 Quantum Programming 🧮 Quantum Algorithms 🔐 Quantum Cryptography 🤖 Quantum Machine Learning

Hands-On Quantum Information Processing with Python

Python for quantum computing: from qubits to algorithms, cryptography, and machine learning.

저자: Dr. Makhamisa Senekane 2021 252 페이지

4.00

1 개의 평점

⚛️ Quantum Computing 💻 Quantum Programming 🧮 Quantum Algorithms 🔐 Quantum Cryptography 🤖 Quantum Machine Learning

Python Machine Learning Case Studies

저자: Danish Haroon • 2017

Five Python case studies in machine learning: from data cleanup to a scored model, step by step.

2.60

📊 Data Science 🤖 Machine Learning 🔍 Exploratory Data Analysis ⚙️ Feature Engineering 📐 Model Evaluation

Python Machine Learning Case Studies

Five Python case studies in machine learning: from data cleanup to a scored model, step by step.

저자: Danish Haroon 2017 221 페이지

2.60

5 개의 평점

📊 Data Science 🤖 Machine Learning 🔍 Exploratory Data Analysis ⚙️ Feature Engineering 📐 Model Evaluation

Practical Data Analytics for BFSI

저자: Mr. Bharat Sikka • 2023

ATM refills, fraud alerts, loan approvals: the data models that run a modern bank.

🏦 Banking Analytics 💼 Financial Services 🗂️ Data Governance 🕵️ Fraud Detection ⚠️ Risk Management

Practical Data Analytics for BFSI

ATM refills, fraud alerts, loan approvals: the data models that run a modern bank.

저자: Mr. Bharat Sikka 2023 334 페이지

🏦 Banking Analytics 💼 Financial Services 🗂️ Data Governance 🕵️ Fraud Detection ⚠️ Risk Management

Java Deep Learning Essentials

저자: Yusuke Sugomori • 2016

Python demos deep learning; Java deploys it. Architectures and libraries to close the gap.

3.20

🧠 Deep Learning ☕ Java Machine Learning 🔧 Practical Deep Learning 👁️ Computer Vision 🗣️ Natural Language Processing

Java Deep Learning Essentials

Python demos deep learning; Java deploys it. Architectures and libraries to close the gap.

저자: Yusuke Sugomori 2016 254 페이지

3.20

5 개의 평점

🧠 Deep Learning ☕ Java Machine Learning 🔧 Practical Deep Learning 👁️ Computer Vision 🗣️ Natural Language Processing

Arcadia

저자: Tom Stoppard • 1993

A Regency prodigy glimpses chaos. Two centuries later, rival scholars in her house chase her truth.

4.13

24,000+

📚 Dual Timeline Narrative 🎭 Comedy Of Manners 🏛️ Country House Drama 🍎 Tutor And Prodigy 📝 Academic Rivals

Arcadia

A Regency prodigy glimpses chaos. Two centuries later, rival scholars in her house chase her truth.

저자: Tom Stoppard 1993 144 페이지

4.13

24,000+ 개의 평점

📚 Dual Timeline Narrative 🎭 Comedy Of Manners 🏛️ Country House Drama 🍎 Tutor And Prodigy 📝 Academic Rivals

Machine Learning

저자: Dr Ruchi Doshi • 2021

From training models with labeled data to finding hidden patterns: the algorithms behind modern AI.

5.00

🧠 Machine Learning 📊 Supervised Learning 🧬 Deep Learning 🕹️ Reinforcement Learning 🛠️ Feature Engineering

Machine Learning

From training models with labeled data to finding hidden patterns: the algorithms behind modern AI.

저자: Dr Ruchi Doshi 2021 294 페이지

5.00

1 개의 평점

🧠 Machine Learning 📊 Supervised Learning 🧬 Deep Learning 🕹️ Reinforcement Learning 🛠️ Feature Engineering

Hyperreality

저자: Mike Hockney • 2012

Reality is a self-solving mathematical equation, and God is the answer, not the author.

4.61

🔢 Mathematical Platonism 🕯️ Esoteric Philosophy ⚛️ Quantum Consciousness 🌐 Holographic Universe 🌊 Process Philosophy

Hyperreality

Reality is a self-solving mathematical equation, and God is the answer, not the author.

저자: Mike Hockney 2012 213 페이지

4.61

56 개의 평점

🔢 Mathematical Platonism 🕯️ Esoteric Philosophy ⚛️ Quantum Consciousness 🌐 Holographic Universe 🌊 Process Philosophy

The Hidden Geometry of Life

저자: Karen L. French • 2012

The cosmos is written in geometry. Three shapes frame reality; one spiral drives its motion.

3.67

🧱 Sacred Geometry 🕉️ Perennial Philosophy 🔬 Metaphysical Science ⚗️ Hermeticism 🌿 Patterns In Nature

The Hidden Geometry of Life

The cosmos is written in geometry. Three shapes frame reality; one spiral drives its motion.

저자: Karen L. French 2012 240 페이지

3.67

55 개의 평점

🧱 Sacred Geometry 🕉️ Perennial Philosophy 🔬 Metaphysical Science ⚗️ Hermeticism 🌿 Patterns In Nature

The Course

저자: Ed Miller • 2015

Profit in poker comes from one source: opponents who play too many hands. Here's the system.

4.40

259

♠️ Poker Strategy 🃏 No Limit Hold Em 💰 Cash Games 🎯 Exploitative Play 📏 Bet Sizing

The Course

Profit in poker comes from one source: opponents who play too many hands. Here's the system.

저자: Ed Miller 2015 306 페이지

4.40

259 개의 평점

♠️ Poker Strategy 🃏 No Limit Hold Em 💰 Cash Games 🎯 Exploitative Play 📏 Bet Sizing

The Survival Game

저자: David Philip Barash • 2003

The logic behind why animals cooperate, nations arm, and rational people sabotage themselves.

3.84

🧮 Game Theory 🧬 Evolutionary Biology 🧠 Behavioral Science 🤝 Cooperation Dilemmas 🏘️ Social Dilemmas

The Survival Game

The logic behind why animals cooperate, nations arm, and rational people sabotage themselves.

저자: David Philip Barash 2003 320 페이지

3.84

44 개의 평점

🧮 Game Theory 🧬 Evolutionary Biology 🧠 Behavioral Science 🤝 Cooperation Dilemmas 🏘️ Social Dilemmas

Godel's Proof

저자: Ernest Nagel • 1958

Arithmetic cannot prove its own consistency. The man who proved that was twenty-five.

4.19

5,000+

🧮 Mathematical Logic 🏛️ Foundations Of Mathematics 🧩 Incompleteness 🪞 Self-Reference ⚙️ Formal Systems

Godel's Proof

Arithmetic cannot prove its own consistency. The man who proved that was twenty-five.

저자: Ernest Nagel 1958 160 페이지

4.19

5,000+ 개의 평점

🧮 Mathematical Logic 🏛️ Foundations Of Mathematics 🧩 Incompleteness 🪞 Self-Reference ⚙️ Formal Systems

AI in the Financial Markets

저자: Federico Cecconi • 2023

AI finds market patterns invisible to humans, trades on them instantly, and offers no explanation.

📉 Financial Markets 💻 Fintech 🤖 Algorithmic Trading 📊 Quantitative Finance 📡 Alternative Data

AI in the Financial Markets

AI finds market patterns invisible to humans, trades on them instantly, and offers no explanation.

저자: Federico Cecconi 2023 236 페이지

📉 Financial Markets 💻 Fintech 🤖 Algorithmic Trading 📊 Quantitative Finance 📡 Alternative Data

The Light Ages

저자: Seb Falk • 2020

Eclipse math, precision clocks, a six-foot computer: the medieval laboratory inside the monastery.

3.67

1,000+

🔬 History Of Science 🏰 Medieval History ⚗️ Medieval Science ⚙️ Medieval Technology 📜 Monastic Scholarship

The Light Ages

Eclipse math, precision clocks, a six-foot computer: the medieval laboratory inside the monastery.

저자: Seb Falk 2020 392 페이지

3.67

1,000+ 개의 평점

🔬 History Of Science 🏰 Medieval History ⚗️ Medieval Science ⚙️ Medieval Technology 📜 Monastic Scholarship

Forecasting

저자: Rob J. Hyndman • 2013

Build forecasts that work: test on unseen data, beat simple benchmarks, reconcile every level.

4.39

318

🧮 Time Series Analysis 📈 Business Forecasting 📊 Statistical Modeling 👁 Data Visualization 📦 Demand Planning

Forecasting

Build forecasts that work: test on unseen data, beat simple benchmarks, reconcile every level.

저자: Rob J. Hyndman 2013 292 페이지

4.39

318 개의 평점

🧮 Time Series Analysis 📈 Business Forecasting 📊 Statistical Modeling 👁 Data Visualization 📦 Demand Planning

Digital Games and Mathematics Learning

저자: Lowrie • 2015

Digital games sharpen the spatial skills math requires, but picking the right app is the hard part.

4.00

🧮 Math Education 🎮 Game-Based Learning 💻 Educational Technology 🧑‍🏫 Teacher Training 🧠 Spatial Reasoning

Digital Games and Mathematics Learning

Digital games sharpen the spatial skills math requires, but picking the right app is the hard part.

저자: Lowrie 2015 326 페이지

4.00

1 개의 평점

🧮 Math Education 🎮 Game-Based Learning 💻 Educational Technology 🧑‍🏫 Teacher Training 🧠 Spatial Reasoning

Human Behavior and the Principle of Least Effort

저자: George Kingsley Zipf • 2012

Every word spoken and every city built follows one mathematical equation.

3.77

📊 Quantitative Linguistics ⚛️ Social Physics 📈 Power Laws 🏙️ Urban Scaling 🗣️ Word Frequencies

Human Behavior and the Principle of Least Effort

Every word spoken and every city built follows one mathematical equation.

저자: George Kingsley Zipf 2012 588 페이지

3.77

22 개의 평점

📊 Quantitative Linguistics ⚛️ Social Physics 📈 Power Laws 🏙️ Urban Scaling 🗣️ Word Frequencies

Machine Trading

저자: Ernest P. Chan • 2016

Why most backtest profits vanish in live trading, and the quantitative methods that survive.

3.83

🤖 Algorithmic Trading 📊 Quantitative Finance 🔁 Backtesting Frameworks ⚠️ Risk Management 🧠 Machine Learning Finance

Machine Trading

Why most backtest profits vanish in live trading, and the quantitative methods that survive.

저자: Ernest P. Chan 2016 256 페이지

3.83

80 개의 평점

🤖 Algorithmic Trading 📊 Quantitative Finance 🔁 Backtesting Frameworks ⚠️ Risk Management 🧠 Machine Learning Finance

The Economist Numbers Guide

저자: The Economist • 2001

A 50% raise then 50% cut leaves you at 75%. The business math that stops costly errors.

3.84

🧮 Quantitative Methods 📊 Business Statistics 🎲 Probability For Managers 🔮 Forecasting Methods 🤔 Decision Analysis

The Economist Numbers Guide

A 50% raise then 50% cut leaves you at 75%. The business math that stops costly errors.

저자: The Economist 2001 271 페이지

3.84

67 개의 평점

🧮 Quantitative Methods 📊 Business Statistics 🎲 Probability For Managers 🔮 Forecasting Methods 🤔 Decision Analysis

High Speed Signal Propagation

저자: Howard W. Johnson • 2003

Your traces are never just wires: the physics that decide whether your board works.

4.00

📡 High-Speed Digital 〰️ Signal Integrity ⚡ Power Integrity 🛡️ Emc 📐 Pcb Layout

High Speed Signal Propagation

Your traces are never just wires: the physics that decide whether your board works.

저자: Howard W. Johnson 2003 808 페이지

4.00

16 개의 평점

📡 High-Speed Digital 〰️ Signal Integrity ⚡ Power Integrity 🛡️ Emc 📐 Pcb Layout

Corporate Capital Structures in the United States

저자: Benjamin M. Friedman • 2009

Inflation turned corporate debt into a tax shelter: the hidden engine of postwar borrowing.

3.50

🏢 Corporate Finance 📊 Capital Structure 💰 Corporate Taxation 📈 Option Pricing Theory 🔍 Agency Costs

Corporate Capital Structures in the United States

Inflation turned corporate debt into a tax shelter: the hidden engine of postwar borrowing.

저자: Benjamin M. Friedman 2009 390 페이지

3.50

2 개의 평점

🏢 Corporate Finance 📊 Capital Structure 💰 Corporate Taxation 📈 Option Pricing Theory 🔍 Agency Costs

Paul Wilmott on Quantitative Finance, Volumes 1-3

저자: Paul Wilmott • 2000

Your hedged portfolio isn't risk-free. Here's why, and the math that explains what actually breaks.

4.25

📈 Derivatives Pricing ⚙️ Financial Engineering 📐 Stochastic Calculus 📊 Volatility Modeling 🛡️ Risk Management

Paul Wilmott on Quantitative Finance, Volumes 1-3

Your hedged portfolio isn't risk-free. Here's why, and the math that explains what actually breaks.

저자: Paul Wilmott 2000 1500 페이지

4.25

81 개의 평점

📈 Derivatives Pricing ⚙️ Financial Engineering 📐 Stochastic Calculus 📊 Volatility Modeling 🛡️ Risk Management

The Numbers Game

저자: David Sally • 2013

Why soccer's weakest player matters more than its star, and half the result is luck.

3.72

3,000+

🎯 Soccer Analytics 💰 Sports Economics 🔗 Team Interdependence 🥷 Underdog Strategies 🎲 Role Of Luck

The Numbers Game

Why soccer's weakest player matters more than its star, and half the result is luck.

저자: David Sally 2013 401 페이지

3.72

3,000+ 개의 평점

🎯 Soccer Analytics 💰 Sports Economics 🔗 Team Interdependence 🥷 Underdog Strategies 🎲 Role Of Luck

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