Benford's Law |
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v | |
Foreword |
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vii | |
Introduction |
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ix | |
Acknowledgment |
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xiii | |
Section 1: Benford's Law |
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1 | (76) |
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3 | (2) |
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2 To Find Fraud, Simply Examine Its Digits! |
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5 | (3) |
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8 | (1) |
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4 Empirical Evidence from Real-Life Data on Digit Distribution |
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9 | (6) |
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5 Physical Clues of the Digital Pattern |
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15 | (3) |
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6 Historical Background of the Two Discoverers |
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18 | (3) |
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21 | (8) |
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8 The Prevalence of Benford's Law |
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29 | (2) |
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9 Physical Law versus Numerical Law |
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31 | (2) |
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10 Nature's Way of Counting Single-Issue Phenomena |
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33 | (5) |
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11 Case Study I: Time Between Earthquakes |
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38 | (3) |
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12 Data on Population Counts of Cities, Towns, Regions, and Districts |
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41 | (1) |
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13 Case Study II: U.S. Census Data on Population Centers |
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42 | (4) |
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14 Data sets on USA Population by State and by County |
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46 | (2) |
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15 Four Distinct Numerical Processes Leading to Benford |
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48 | (1) |
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16 Random Linear Combinations and Accounting Revenue Data |
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49 | (4) |
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17 Aggregation of Data Sets as a Prominent Cause of Benford's Law |
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53 | (2) |
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18 Random Pick from a Variety of Data Sources is Logarithmic |
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55 | (2) |
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19 Integral Powers of Ten |
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57 | (1) |
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20 The Logarithmic as Repeated Multiplications |
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58 | (9) |
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21 Case Study III: Exponential 0.5% Growth Series for 3,233 Periods |
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67 | (3) |
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22 Case Study IV: 140 Cumulative Dice Multiplications |
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70 | (2) |
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23 The Universality of Benford's Law -True in any Scale System |
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72 | (2) |
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24 A Hidden Digital Signature within Benford's Digital Signature |
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74 | (3) |
Section 2: Forensic Digital Analysis & Fraud Detection |
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77 | (36) |
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25 Historical Background of the First Applications of Benford's Law |
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79 | (2) |
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26 Methods in Financial and Accounting Fraud Detection |
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81 | (7) |
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27 The Part and Type of Data Applicable to Forensic Testing |
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88 | (8) |
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28 Case Study V: U.S. Market Capitalization on January 1, 2013 |
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96 | (2) |
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29 Case Study VI: Microsoft Corporation Financial Statement |
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98 | (2) |
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30 Case Study VII: Total Return of Athena Guaranteed Futures Fund |
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100 | (2) |
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31 Establishing Direct Connection Between Digit Anamoly & Fraud |
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102 | (4) |
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106 | (2) |
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33 Detecting Fraud via Digital Development Pattern |
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108 | (2) |
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34 The Dilemma of FTD versus LTD for Digit-Anemic Numbers |
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110 | (3) |
Section 3: Data Compliance Tests |
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113 | (82) |
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35 Testing Data for Conformity to Benford's Law |
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115 | (5) |
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120 | (3) |
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123 | (5) |
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38 SSD as a Measure of Distance from the Logarithmic |
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128 | (6) |
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39 Saville Regression Measure |
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134 | (4) |
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138 | (3) |
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41 The Confusion and Mistaken Applications of Summation Test |
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141 | (6) |
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42 Summation Test in the Context of Fraud Detection |
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147 | (2) |
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43 Methods in Digital Development Pattern Detection |
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149 | (15) |
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44 Case Study VIII: Price List of a Large Manufacturer |
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164 | (8) |
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45 Case Study IX: USA County Area Data |
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172 | (5) |
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46 Random Linear Combinations and Revenue Data Revisited |
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177 | (15) |
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47 Case Study X: Forensic Analysis of Revenue Data for Small Shop |
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192 | (3) |
Section 4: Conceptual and Mathematical Foundations |
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195 | (178) |
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48 Hybrid Data Sets Blending Several Data Types |
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197 | (1) |
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49 Second-Generation Distributions |
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198 | (2) |
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50 A Leading Digits Parable |
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200 | (7) |
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51 Simple Averaging Scheme as a Model for Typical Data |
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207 | (5) |
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52 More Complex Averaging Schemes |
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212 | (4) |
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53 Digital Proportions within the Number System Itself |
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216 | (3) |
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54 Chains of Distributions |
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219 | (8) |
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55 Hill's Super Distribution |
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227 | (3) |
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56 The Scale Invariance Principle |
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230 | (3) |
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57 Philosophical and Conceptual Observations |
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233 | (4) |
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237 | (5) |
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59 Density Curves and Their Leading Digits Distributions |
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242 | (4) |
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60 The Case of k/x Distribution |
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246 | (7) |
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61 Uniform Mantissa, Varied Significand, and the General Law |
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253 | (8) |
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62 Uniqueness of k/x Distribution |
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261 | (5) |
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63 Related Log Conjecture |
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266 | (5) |
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64 Testing Related Log Conjecture via Simulations |
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271 | (4) |
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65 The Lognormal Conjecture of Hill's Super Distribution |
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275 | (4) |
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66 Non-Symmetric Related Log Curves |
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279 | (2) |
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67 Wide Range on the Log-Axis and Logarithmic Behavior |
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281 | (1) |
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68 The Remarkable Malleability of Related Log Conjecture |
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282 | (11) |
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69 Hill's Super Distribution and Related Log Conjecture |
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293 | (2) |
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70 Scale Invariance Principle and Related Log Conjecture |
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295 | (2) |
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71 The Near Indestructibility of Higher Order Distributions |
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297 | (4) |
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72 Falling Density Curve with a Tail to the Right |
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301 | (4) |
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73 Falling Density Curve with a Particular Steepness |
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305 | (2) |
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74 Fall in Density is Well-Coordinated Between IPOT Values |
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307 | (6) |
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75 Synthesis Between the Deterministic and the Random |
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313 | (4) |
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76 Dichotomy Between the Deterministic and the Random |
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317 | (10) |
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77 Fitting the Random into the Deterministic |
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327 | (5) |
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78 The Random Flavor of Population Data |
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332 | (3) |
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79 The Lognormal Distribution and Benford's Law |
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335 | (4) |
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80 Scrutinizing Digits within Lognormal, Exponential, and k/x |
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339 | (6) |
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81 Leading Digits Inflection Point |
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345 | (4) |
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82 Digital Development Pattern Found in all Real-Life Random Data |
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349 | (7) |
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83 Digital Development Pattern Seen Only Under IPOT Partition |
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356 | (4) |
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84 Development Pattern More Prevalent than Benford's Law Itself |
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360 | (3) |
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85 Sum-Invariant Characterization of the Law (Summation Test) |
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363 | (10) |
Section 5: Benford's Law in the Physical Sciences |
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373 | (52) |
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86 Mother Nature Builds and Destroys with Digits in Mind |
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375 | (2) |
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87 Quantum Mechanics, Thermodynamics, and Benford's Law |
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377 | (3) |
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88 Chemistry, Random Linear Combinations, and Benford's Law |
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380 | (7) |
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89 Benford's Law and the Set of all Physical Constants |
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387 | (2) |
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90 MCLT as an Explanation for Single-Issue Physical Phenomenon |
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389 | (6) |
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91 Chains as an Explanation for Single-Issue Physical Phenomenon |
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395 | (3) |
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92 Breaking a Rock Repeatedly into Small Pieces is Logarithmic |
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398 | (4) |
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93 Random Throw of Balls into Boxes Approximating the Logarithmic |
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402 | (13) |
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94 Logarithmic Model for Planet and Star Formations |
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415 | (4) |
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95 Hybrid Causes Leading to Logarithmic Convergence |
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419 | (2) |
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96 Mild Deviations Seen in Small Samples of Logarithmic Data Sets |
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421 | (2) |
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97 The Remarkable Versatility of Benford's Law |
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423 | (2) |
Section 6: Topics in Benford's Law |
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425 | (84) |
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98 Singularities in Exponential Growth Series |
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427 | (12) |
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99 Super Exponential Growth Series |
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439 | (3) |
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100 Higher-Order Leading Digits |
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442 | (10) |
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101 Digit Distributions Assuming Other Bases 450 |
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102 Chains of Distributions Revisited |
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452 | (10) |
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103 Chainable Distributions and Parameters |
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462 | (9) |
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104 Frank Benford's Averaging Scheme as a Distribution Chain |
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471 | (3) |
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105 Effects of Parametrical Transformations on Leading Digits |
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474 | (5) |
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106 Digits of the Wald, Weibull, chi-square, and Gamma Distributions |
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479 | (1) |
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107 Digital Patterns of the Exponential Distribution |
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480 | (17) |
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108 Saville Regression Measure Revisited 484- |
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109 The Scale Invariance Principle and AGD Interpretation |
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497 | (4) |
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110 Case Study XI: Large Sample from a Variety of Data Sources |
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501 | (5) |
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111 Direct Expression of first Digit for any Number - Computer Use |
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506 | (1) |
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112 Artificially Creating Nearly Perfect Logarithmic Data |
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507 | (2) |
Section 7: The Law of Relative Quantities |
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509 | (128) |
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113 The Relating Concepts of Digits, Numbers, and Quantities |
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511 | (2) |
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114 Benford's Law in its Purest Form |
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513 | (6) |
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115 Number System Invariance Principle |
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519 | (3) |
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116 Cartesian Coordinate System is Number-System-Invariant |
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522 | (2) |
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117 Physics is Number-System-Invariant |
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524 | (3) |
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118 Multiplicative CLT is Number-System-Invariant |
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527 | (2) |
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119 Greek Parable and Chains are Number-System-Invariant |
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529 | (1) |
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120 Physical Reality versus Digital Perception |
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530 | (1) |
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121 Patterns in Physical Data Transcend Number Systems and Digits |
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531 | (1) |
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122 Common Thread Going Through Multiple Physical Data Sets |
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532 | (3) |
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123 Casting a Repetitive Bin System to Measure Fall in Histogram |
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535 | (7) |
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124 Non-Expanding Bin System Measuring Fall in k/x Distribution |
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542 | (5) |
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125 Once-Expanding Bin System Measuring Fall in k/x Distribution |
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547 | (2) |
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126 Once-Expanding Bins for k/x Reduces to Benford when F = D + 1 |
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549 | (1) |
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127 Twice-Expanding Bin System Measuring Fall in k/x Distribution |
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550 | (2) |
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128 Twice-Expanding Bins for k/x Reduces to Benford when F = D + 1 |
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552 | (2) |
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129 Infinitely Expanding Bin System Measuring Fall in k/x |
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554 | (2) |
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130 Confirmation Matching k/x Fall with Empirical Bins on Real Data |
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556 | (2) |
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131 Closed Form Expression for the Limit of the Infinite Sequence |
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558 | (5) |
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132 Closed Form Expression for the Limit in the Flat Case F = 1 |
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563 | (4) |
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133 9-Bin Systems with F = 10 on Real Data All Yield LOGTEN(1+1/d) |
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567 | (2) |
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134 Bin Systems Need to Start Near Origin with Small Initial Width |
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569 | (6) |
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135 Actual or Degree of Compliance May Be Bin- and Base-Variant |
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575 | (7) |
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136 Correspondence in Data Classification Between Bin Systems and BL |
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582 | (8) |
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137 F = D + 1 Bin Systems on Real DataYield LOGBAsE(1+1/d) |
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590 | (1) |
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138 The Remarkable Malleability and Universality of Bin Schemes |
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591 | (11) |
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139 Higher-Order Digits Interpreted as Particular Bin Schemes |
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602 | (6) |
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140 Bin Development Pattern |
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608 | (6) |
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141 The General Scale Invariance Principle |
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614 | (5) |
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619 | (3) |
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143 Digits Serving as Quantities in Benford's Law |
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622 | (2) |
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144 Frank Benford's Prophetic Words |
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624 | (1) |
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625 | (1) |
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146 The Universal Law of Relative Quantities |
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626 | (2) |
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147 Dialogue Concerning the Two Chief Statistical Systems |
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628 | (9) |
References |
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637 | (6) |
Glossary of Frequently Used Abbreviations |
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643 | (2) |
Index |
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645 | |