Martin B.R. Statistics for physical sciences: an introduction (Amsterdam; Boston, 2012). - ОГЛАВЛЕНИЕ / CONTENTS
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ОбложкаMartin B.R. Statistics for physical sciences: an introduction. - Amsterdam; Boston: Elsevier/Academic Press, 2012. - x, 302 p.: ill. - Bibliogr.: p.293-294. - Ind.: p.295-302. - ISBN 978-0-12-387760-4
 

Оглавление / Contents
 
Preface ........................................................ ix
1  Statistics, Experiments, and Data ............................ 1
   1.1  Experiments and Observations ............................ 2
   1.2  Displaying Data ......................................... 4
   1.3  Summarizing Data Numerically ............................ 7
        1.3.1  Measures of Location ............................. 8
        1.3.2  Measures of Spread ............................... 9
        1.3.3  More than One Variable .......................... 12
   1.4  Large Samples .......................................... 15
   1.5  Experimental Errors .................................... 17
   Problems 1 .................................................. 19
2  Probability ................................................. 21
   2.1  Axioms of Probability .................................. 21
   2.2  Calculus of Probabilities .............................. 23
   2.3  The Meaning of Probability ............................. 27
        2.3.1  Frequency Interpretation ........................ 27
        2.3.2  Subjective Interpretation ....................... 29
   Problems 2 .................................................. 32
3  Probability Distributions I: Basic Concepts ................. 35
   3.1  Random Variables ....................................... 35
   3.2  Single Variates ........................................ 36
        3.2.1  Probability Distributions ....................... 36
        3.2.2  Expectation Values .............................. 40
        3.2.3  Moment Generating, and Characteristic
               Functions ....................................... 42
   3.3  Several Variates ....................................... 45
        3.3.1  Joint Probability Distributions ................. 45
        3.3.2  Marginal and Conditional Distributions .......... 45
        3.3.3  Moments and Expectation Values .................. 49
   3.4  Functions of a Random Variable ......................... 51
   Problems 3 .................................................. 55
4  Probability Distributions II: Examples ...................... 57
   4.1  Uniform ................................................ 57
   4.2  Univariate Normal (Gaussian) ........................... 59
   4.3  Multivariate Normal .................................... 63
        4.3.1  Bivariate Normal ................................ 65
   4.4  Exponential ............................................ 66
   4.5  Cauchy ................................................. 68
   4.6  Binomial ............................................... 69
   4.7  Multinomial ............................................ 74
   4.8  Poisson ................................................ 75
   Problems 4 .................................................. 80
5  Sampling and Estimation ..................................... 83
   5.1  Random Samples and Estimators .......................... 83
        5.1.1  Sampling Distributions .......................... 84
        5.1.2  Properties of Point Estimators .................. 86
   5.2  Estimators for the Mean, Variance, and Covariance ...... 90
   5.3  Laws of Large Numbers and the Central Limit Theorem .... 93
   5.4  Experimental Errors .................................... 97
        5.4.1  Propagation of Errors ........................... 99
   Problems 5 ................................................. 103
6  Sampling Distributions Associated with the Normal
   Distribution ............................................... 105
   6.1  Chi-Squared Distribution .............................. 105
   6.2  Student's t Distribution .............................. 111
   6.3  F Distribution ........................................ 116
   6.4  Relations Between x2, t, and F Distributions .......... 119
        Problems 6 ............................................ 121
7  Parameter Estimation I: Maximum Likelihood and Minimum
   Variance ................................................... 123
   7.1  Estimation of a Single Parameter ...................... 123
   7.2  Variance of an Estimator .............................. 128
        7.2.1  Approximate methods ............................ 130
   7.3  Simultaneous Estimation of Several Parameters ......... 133
   7.4  Minimum Variance ...................................... 136
        7.4.1  Parameter Estimation ........................... 136
        7.4.2  Minimum Variance Bound 137
   Problems 7 ................................................. 140
8  Parameter Estimation II: Least-Squares and Other Methods ... 143
   8.1  Unconstrained Linear Least Squares .................... 143
        8.1.1  General Solution for the Parameters ............ 145
        8.1.2  Errors on the Parameter Estimates .............. 149
        8.1.3  Quality of the Fit ............................. 151
        8.1.4  Orthogonal Polynomials ......................... 152
        8.1.5  Fitting a Straight Line ........................ 154
        8.1.6  Combining Experiments .......................... 158
   8.2  Linear Least Squares with Constraints ................. 159
   8.3  Nonlinear Least Squares ............................... 162
   8.4  Other Methods ......................................... 163
        8.4.1  Minimum Chi-Square ............................. 163
        8.4.2  Method of Moments .............................. 165
        8.4.3  Bayes' Estimators .............................. 167
   Problems 8 ................................................. 171
9  Interval Estimation ........................................ 173
   9.1  Confidence Intervals: Basic Ideas ..................... 174
   9.2  Confidence Intervals: General Method .................. 177
   9.3  Normal Distribution ................................... 179
        9.3.1  Confidence Intervals for the Mean .............. 180
        9.3.2  Confidence Intervals for the Variance .......... 182
        9.3.3  Confidence Regions for the Mean and Variance ... 183
   9.4  Poisson Distribution .................................. 184
   9.5  Large Samples ......................................... 186
   9.6  Confidence Intervals Near Boundaries .................. 187
   9.7  Bayesian Confidence Intervals ......................... 189
   Problems 9 ................................................. 190
10 Hypothesis Testing I: Parameters ........................... 193
   10.1 Statistical Hypotheses ................................ 194
   10.2 General Hypotheses: Likelihood Ratios ................. 198
        10.2.1 Simple Hypothesis: One Simple Alternative ...... 198
        10.2.2 Composite Hypotheses ........................... 201
   10.3 Normal Distribution ................................... 204
        10.3.1 Basic Ideas .................................... 204
        10.3.2 Specific Tests ................................. 206
   10.4 Other Distributions ................................... 214
   10.5 Analysis of Variance .................................. 215
   Problems 10 ................................................ 218
11 Hypothesis Testing II: Other Tests ......................... 221
   11.1 Goodness-of-Fit Tests ................................. 221
        11.1.1 Discrete Distributions ......................... 222
        11.1.2 Continuous Distributions ....................... 225
        11.1.3 Linear Hypotheses .............................. 228
   11.2 Tests for Independence ................................ 231
   11.3 Nonparametric Tests ................................... 233
        11.3.1 Sign Test ...................................... 233
        11.3.2 Signed-Rank Test ............................... 234
        11.3.3 Rank-Sum Test .................................. 236
        11.3.4 Runs Test ...................................... 237
        11.3.5 Rank Correlation Coefficient ................... 239
   Problems 11 ................................................ 241
Appendix A. Miscellaneous Mathematics ......................... 243
   A.l  Matrix Algebra ........................................ 243
   A.2  Classical Theory of Minima ............................ 247
Appendix B. Optimization of Nonlinear Functions ............... 249
   B.l  General Principles .................................... 249
   B.2  Unconstrained Minimization of Functions of One
        variable .............................................. 252
   B.3  Unconstrained Minimization of Multivariable
        Functions ............................................. 253
        B.3.1  Direct Search Methods .......................... 253
        B.3.2  Gradient Methods ............................... 254
   B.4  Constrained Optimization .............................. 255
Appendix C. Statistical Tables ................................ 257
   С.1  Normal Distribution ................................... 257
   C.2  Binomial Distribution ................................. 259
   C.3  Poisson Distribution .................................. 266
   C.4  Chi-squared Distribution .............................. 273
   C.5  Student's t Distribution .............................. 275
   C.6  F Distribution ........................................ 277
   C.7  Signed-Rank Test ...................................... 283
   C.8  Rank-Sum Test ......................................... 284
   C.9  Runs Test ............................................. 285
   C.10 Rank Correlation Coefficient .......................... 286
Appendix D. Answers to Odd-Numbered Problems .................. 287

Bibliography .................................................. 293
Index ......................................................... 295


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