Statistics step by step:
Gespeichert in:
| 1. Verfasser: | |
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| Format: | Buch |
| Sprache: | Undetermined |
| Veröffentlicht: |
Boston
Houghton Mifflin
1977
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| Online-Zugang: | Inhaltsverzeichnis |
| ISBN: | 0395245273 |
Internformat
MARC
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Datensatz im Suchindex
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| adam_text | Titel: Statistics step by step
Autor: Christensen, Howard B
Jahr: 1977
CONTENTS Preface xi To the Student xiii How to Use This Book xv UNIT ONE COLLECTING DATA Lesson One Components of a statistical investigation 2 Lesson Two Parameter versus statistic 8 Lesson Three Random versus nonrandom sampling 12 Lesson Four Simple random samples 16 Lesson Five Experiment or sample survey 22 Lesson Six Sample-to-sample variability 26 Application of what you ve learned 28 Summary 28 Self-test on Unit One 29 Answers to odd-numbered practice problems 30 UNIT TWO GRAPHICAL ORGANIZATION AND SUMMARIZATION OF DATA Lesson One Ordered arrays and stem and leaf arrangements 34 Lesson Two Frequency tables: One variable 41 Lesson Three Bar graphs 49 Lesson Four Histograms and frequency polygons 52 Lesson Five Frequency tables and histograms: Two variables 56 Lesson Six Scatter plots 58 Application of what you ve learned 61 Summary 61 Self-test on Unit Two 62 Answers to odd-numbered practice problems 64 UNIT THREE NUMERICAL SUMMARIZATION OF DATA Lesson One Preliminaries: Subscripted variables and summation notation 72 Lesson Two Rules of summation notation 76 Lesson Three Measures of location: Mean, median, mode 79 Lesson Four Comparing the mean, median, and mode 87 Lesson Five Measures of variability: Range, variance, standard deviation 90 Lesson Six The empirical rule 99 Lesson Seven Proportion and total 105 Lesson Eight Computing sample statistics 109
vi CONTENTS Application of what you ve learned 115 Summary 116 Self-test on Unit Three 117 Answers to odd-numbered practice problems 119 UNIT FOUR BASIC RULES OF PROBABILITY Lesson One Experiments and sample spaces 125 Lesson Two The urn model 133 Lesson Three Simple events and compound events 135 Lesson Four Rules of counting 137 Lesson Five Set operations 147 Lesson Six Probability of simple and compound events in finite sample spaces 153 Lesson Seven Probability of the union and the complement 162 Lesson Eight Conditional probability 168 Lesson Nine Independent events and the probability of their intersection 175 Lesson Ten Solving probability problems 182 Application of what you ve learned 188 Summary 189 Supplement: Formula for counting permutations 191 Self-test on Unit Four 193 Answers to odd-numbered practice problems 195 UNIT FIVE PROBABILITY DISTRIBUTIONS OF RANDOM VARIABLES Lesson One Random variables 204 Lesson Two Probability distributions of a random variable 208 Lesson Three The mean and variance of a probability distribution 216 Lesson Four The normal distribution 223 Lesson Five Determining normal distribution probabilities 231 Lesson Six The binomial distribution 241 Lesson Seven Determining binomial probabilities 245 Lesson Eight The normal approximation to the binomial distribution 251 Application of what you ve learned 257 Summary 258 Self-test on Unit Five 258 Answers to odd-numbered practice problems 260 UNIT SIX SAMPLING DISTRIBUTIONS Lesson One The sampling distribution of the sample mean 266
CONTENTS vii Lesson Two The sampling distribution of the sample proportion 273 Lesson Three The central limit theorem 279 Application of what you ve learned 285 Summary 286 Self-test on Unit Six 287 Answers to odd-numbered practice problems 288 UNIT SEVEN ESTIMATION AND CONFIDENCE INTERVALS Lesson One Unbiased and efficient estimators 293 Lesson Two The standard error 299 Lesson Three The / distribution 302 Lesson Four Using the f-distribution table 306 Lesson Five Confidence intervals: General concepts 310 Lesson Six Confidence interval for the population mean 317 Lesson Seven Large-sample confidence interval for the population total 324 Lesson Eight Large-sample confidence interval for the proportion 327 Lesson Nine Confidence interval for the difference between two means 330 Lesson Ten Confidence interval for the difference between two proportions 337 Lesson Eleven How large a sample? 341 Application of what you ve learned 345 Summary 345 Self-test on Unit Seven 346 Answers to odd-numbered practice problems 349 UNIT EIGHT TESTS OF HYPOTHESES ABOUT MEANS OF NORMAL DISTRIBUTIONS Lesson One Levels of measurement 357 Lesson Two Step 1: Formulating the hypothesis 362 Lesson Three Type I and type II errors 367 Lesson Four Steps 2-6: Test statistics and decision rules 370 Lesson Five One-tailed versus two-tailed tests 375 Lesson Six The probability of errors: a and ft 378 Lesson Seven Estimation versus tests of hypothesis 390 Lesson Eight A test for one mean when o is known 392 Lesson Nine A small-sample test for one mean when a is unknown 401 Lesson Ten A test for two means when samples are independent 411 Lesson Eleven A test for two means when observations are paired 423 Application of what you ve learned 435 Summary 435 Self-test on Unit Eight 436 Answers to odd-numbered practice problems 440
viii CONTENTS UNIT NINE CATEGORICAL DATA AND THEIR TESTS Lesson One A large-sample approximate test for one proportion 448 Lesson Two A large-sample approximate test for two proportions 452 Lesson Three The chi-square distribution and approximate test statistics for categorical 457 data Lesson Four A large-sample chi-square test for the multinomial distribution 461 Lesson Five A chi-square test for contingency tables 466 Application of what you ve learned 476 Summary 477 Self-test on Unit Nine 478 Answers to odd-numbered practice problems 482 UNIT TEN ANALYSIS OF VARIANCE __ Lesson One The variance ratio and the F distribution 487 Lesson Two Basic terminology for designing experiments 493 Lesson Three Design and analysis of variance: The statistical model 497 Lesson Four Concept of analysis of variance 500 Lesson Five Completely randomized design: Equal sample sizes 508 Lesson Six Completely randomized design: Unequal sample sizes 516 Lesson Seven Newman-Keuls multiple comparison procedure 521 Lesson Eight Randomized block design 529 Application of what you ve learned 535 Summary 536 Self-test on Unit Ten 537 Answers to odd-numbered practice problems 540 UNIT ELEVEN REGRESSION AND CORRELATION Lesson One Dependent versus independent variables: The scatter plot 546 Lesson Two Simple linear regression and the least-squares regression line 553 Lesson Three The variance term 562 Lesson Four The adjusted and unadjusted coefficient of determination 568 Lesson Five Assumptions for inference 575 Lesson Six Confidence interval for u . 578 y X ° Lesson Seven Prediction interval for a single value of y 582 Lesson Eight Inference about and /ij 586 Lesson Nine Properties of the correlation coefficient 591 Lesson Ten Pearson s correlation coefficient 595 Lesson Eleven Testing a correlation hypothesis 599 Application of what you ve learned 601 Summary 602 Self-test on Unit Eleven 603 Answers to odd-numbered practice problems 608
ix 614 619 624 628 632 638 638 639 641 A.l 1.1 NONPARAMETRIC TESTS The sign test The Wilcoxon matched-pairs, signed-rank test The Wilcoxon two-sample, rank-sum test The runs test Spearman s rank-correlation coefficient Application of what you ve learned Summary Self-test on Unit Twelve Answers to odd-numbered practice problems APPENDIX Tables INDEX
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| illustrated | Not Illustrated |
| indexdate | 2024-07-09T19:46:42Z |
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