Efnisyfirlit

• How to Measure Anything
• Contents
• Preface to the Third Edition
• About the Companion Website
• Acknowledgments
• About the Author
• Part I The Measurement Solution Exists
  • Chapter 1 The Challenge of Intangibles
    • The Alleged Intangibles
    • Yes, I Mean Anything
    • The Proposal: It’s about Decisions
    • A “Power Tools” Approach to Measurement
    • A Guide to the Rest of the Book
  • Chapter 2 An Intuitive Measurement Habit: Eratosthenes, Enrico, and Emily
    • How an Ancient Greek Measured the Size of Earth
    • Estimating: Be Like Fermi
    • Experiments: Not Just for AduLts
    • Notes on What to Learn from Eratosthenes, Enrico, and Emily
    • Notes
  • Chapter 3 The Illusion of Intangibles: Why Immeasurables Aren’t
    • The Concept of Measurement
    • A Definition of Measurement: An “Information Theory” Version
      • A Variety of Measurement Scales
      • Bayesian Measurement: A Pragmatic Concept for Decisions
    • The Object of Measurement
    • The Methods of Measurement
      • The Power of Small Samples: The Rule of Five
      • Even Smaller Samples: The Urn of Mystery
      • Our Small-Sample Intuition versus Math
    • Economic Objections to Measurement
    • The Broader Objection to the Usefulness of “Statistics”
    • Ethical Objections to Measurement
    • Reversing Old Assumptions
      • It’s Been Measured Before
      • You Have Far More Data than You Think
      • You Need Far Less Data than You Think
      • Useful, New Observations Are More Accessible than You Think
    • Notes
• Part II Before You Measure
  • Chapter 4 Clarifying the Measurement Problem
    • Toward a Universal Approach to Measurement
    • The Unexpected Challenge of Defining a Decision
      • Decision-Oriented Measurements: For Scientists, Too
      • How to Get to a Real Decision
      • Requirements for a Decision
      • Potential Forms of a Decision
    • If You Understand it, You Can Model it
    • Getting the Language Right: What “Uncertainty” and “Risk” Really Mean
    • An Example of a Clarified Decision
    • Notes
  • Chapter 5 Calibrated Estimates: How Much Do You Know Now?
    • Calibration Exercise
    • Calibration Trick: Bet Money (or Even Just Pretend To)
    • Further Improvements on Calibration
    • Conceptual Obstacles to Calibration
    • The Effects of Calibration Training
    • Notes
  • Chapter 6 Quantifying Risk through Modeling
    • How Not to Quantify Risk
    • Real Risk Analysis: The Monte Carlo
    • An Example of the Monte Carlo Method and Risk
    • Tools and Other Resources for Monte Carlo Simulations
    • The Risk Paradox and the Need for Better Risk Analysis
    • Notes
  • Chapter 7 Quantifying the Value of Information
    • The Chance of Being Wrong and the Cost of Being Wrong: Expected Opportunity Loss
    • The Value of Information for Ranges
    • Beyond yes/no: Decisions on a Continuum
    • The Imperfect World: The Value of Partial Uncertainty Reduction
      • Perishable Information Values
      • Information Values for Multiple Variables
    • The Epiphany Equation: How the Value of Information Changes Everything
    • Summarizing Uncertainty, RisK, and Information Value: The pre-measurements
    • Notes
• Part III Measurement Methods
  • Chapter 8 The Transition: From What to Measure to How to Measure
    • Tools of Observation: Introduction to the Instrument of Measurement
    • Decomposition
    • Secondary Research: Assuming You Weren’t the First to Measure It
    • The Basic Methods of Observation: If One Doesn’t Work, Try the Next
    • Measure Just Enough
    • Consider the Error
    • Choose and Design the Instrument
    • Note
  • Chapter 9 Sampling Reality: How Observing Some Things Tells Us about All Things
    • Building an Intuition for Random Sampling: The Jelly Bean Example
    • A Little About Little Samples: A Beer Brewer’s Approach
    • Are Small Samples Really “Statistically Significant”?
    • When Outliers Matter Most
    • The Easiest Sample Statistic Ever
    • A Biased Sample of Sampling Methods
      • Population Proportion Sampling
      • Spot Sampling
      • Serial Sampling
      • Measure to the Threshold
      • . . . And a Lot More
    • Experiment
      • An Example Experiment
      • Now, More about the Meaning of Significance
      • The Significance of Emily Rosa’s Experiment: A Counterfactual Outcome
    • Seeing Relationships in the Data: An Introduction to Regression modeling
      • A Regression Example: TV Ratings
      • Parting Thoughts About Regression
    • Notes
  • Chapter 10 Bayes: Adding to What You Know Now
    • The Basics and Bayes
      • Example: Applying Bayes to Market Tests of New Products
      • One More Time: A Bayesian Look at Emily’s Experiment
      • Demystifying the Urn of Mystery
    • Using Your Natural Bayesian Instinct
      • Instinctive Bayesian Approach
    • Heterogeneous Benchmarking: A “Brand Damage” Application
    • Bayesian Inversion for Ranges: An Overview
      • Example: Percentage of Customers Kept After a Change
      • Bayes for Estimates of Means
    • The Lessons of Bayes
      • Myth 1: Absence of Evidence
      • Myth 2: Correlation Is Not Evidence of Causation
      • Myth 3: Ambiguous Results Tell Us Nothing
      • Myth 4: “This Alone Tells Me Nothing”
    • Notes
• Part IV Beyond the Basics
  • Chapter 11 Preference and Attitudes: The Softer Side of Measurement
    • Observing Opinions, Values, and the Pursuit of Happiness
    • A Willingness to Pay: Measuring Value via Trade-Offs
    • Putting It All on the Line: Quantifying Risk Tolerance
    • Quantifying Subjective Trade-Offs: Dealing with Multiple Conflicting Preferences
    • Keeping the Big Picture in Mind: Profit Maximization Versus Purely Subjective Trade-Offs
    • Notes
  • Chapter 12 The Ultimate Measurement Instrument: Human Judges
    • Homo Absurdus: The Weird Reasons behind Our Decisions
    • Getting Organized: A Performance Evaluation Example
    • Surprisingly Simple Linear Models
    • How to Standardize Any Evaluation: Rasch Models
    • Removing Human inconsistency: the Lens Model
    • Panacea or Placebo?: Questionable Methods of Measurement
    • Comparing the Methods
    • Example: A Scientist Measures the Performance of a Decision Model
    • Notes
  • Chapter 13 New Measurement Instruments for Management
    • The Twenty-First-Century Tracker: Keeping Tabs with Technology
    • Measuring the World: The Internet as an Instrument
    • Prediction Markets: A Dynamic Aggregation of Opinions
    • Notes
  • Chapter 14 A Universal Measurement Method: Applied Information Economics
    • Bringing the Pieces Together
    • Case: The Value of the System That Monitors Your Drinking Water
      • Phase 0
      • Phase 1
      • Phase 2
      • Phase 3
      • Epilogue
    • Case: Forecasting Fuel for the Marine Corps
      • Phase 0
      • Phase 1
      • Phase 2
      • Phase 3
      • Epilogue
    • Case: Measuring the Value of Acord Standards
      • Phase 0
      • Phase 1
      • Phase 2
      • Phase 3
      • Epilogue
    • Ideas for Getting Started: A Few Final Examples
      • Quality
      • Value of a Process, Department, or Function
      • Innovation
      • Information Availability
      • Flexibility
      • Flexibility with Options Theory
    • Summarizing the Philosophy
    • Notes
• Appendix: Calibration Tests (and Their Answers)
• Index

UM RAFBÆKUR Á HEIMKAUP.IS

Bókahillan þín er þitt svæði og þar eru bækurnar þínar geymdar. Þú kemst í bókahilluna þína hvar og hvenær sem er í tölvu eða snjalltæki. Einfalt og þægilegt!

Rafbók til eignar
Rafbók til eignar þarf að hlaða niður á þau tæki sem þú vilt nota innan eins árs frá því bókin er keypt.

Þú kemst í bækurnar hvar sem er
Þú getur nálgast allar raf(skóla)bækurnar þínar á einu augabragði, hvar og hvenær sem er í bókahillunni þinni. Engin taska, enginn kyndill og ekkert vesen (hvað þá yfirvigt).

Auðvelt að fletta og leita
Þú getur flakkað milli síðna og kafla eins og þér hentar best og farið beint í ákveðna kafla úr efnisyfirlitinu. Í leitinni finnur þú orð, kafla eða síður í einum smelli.

Glósur og yfirstrikanir
Þú getur auðkennt textabrot með mismunandi litum og skrifað glósur að vild í rafbókina. Þú getur jafnvel séð glósur og yfirstrikanir hjá bekkjarsystkinum og kennara ef þeir leyfa það. Allt á einum stað.

Hvað viltu sjá? / Þú ræður hvernig síðan lítur út
Þú lagar síðuna að þínum þörfum. Stækkaðu eða minnkaðu myndir og texta með multi-level zoom til að sjá síðuna eins og þér hentar best í þínu námi.



Fleiri góðir kostir
- Þú getur prentað síður úr bókinni (innan þeirra marka sem útgefandinn setur)
- Möguleiki á tengingu við annað stafrænt og gagnvirkt efni, svo sem myndbönd eða spurningar úr efninu
- Auðvelt að afrita og líma efni/texta fyrir t.d. heimaverkefni eða ritgerðir
- Styður tækni sem hjálpar nemendum með sjón- eða heyrnarskerðingu