Biostatistical analysis / Jerrold H. Zar.
Editor: Upper Saddle River, N.J. : Prentice Hall, c1999Edición: 4th edDescripción: xii, 663, 212 p. : il. ; 25 cmISBN: 013081542XOtra clasificación: 62-01 (62P10 92B15)1 INTRODUCTION [1] 1.1 Types of Biological Data [2] 1.2 Accuracy and Significant Figures [5] 2 POPULATIONS AND SAMPLES [16] 2.1 Populations [16] 2.2 Samples from Populations [17] 3 MEASURES OF CENTRAL TENDENCY [20] 3.1 The Arithmetic Mean [20] 3.2 The Median [23] 3.3 Other Quantiles [26] 3.4 The Mode [27] 4 MEASURES OF DISPERSION AND VARIABILITY [32] 4.1 The Range [32] 4.2 Dispersion Measured with Quantiles [34] 4.3 The Mean Deviation [34] 4.4 The Variance [35] 4.5 The Standard Deviation [39] 5 PROBABILITIES [48] 5.1 Counting Possible Outcomes [49] 5.2 Permutations [50] 5.3 Combinations [54] SA Sets [56] 6 THE NORMAL DISTRIBUTION [65] 6.1 Symmetry and Kurtosis [67] 6.2 Proportions of a Normal Distribution [72] 6.3 The Distribution of Means [76] 1.3 Frequency Distributions [6] 1.4 Cumulative Frequency Distributions [13] 2.3 Random Sampling [17] 2.4 Parameters and Statistics [18] 3.5 Other Measures of Central Tendency [28] 3.6 The Effect of Coding Data [29] Exercises [31] The Coefficient of Variation [40] Indices of Diversity [40] The Effect of Coding Data [44] Exercises [47] 5.5 Probability of an Event [58] 5.6 Adding Probabilities [59] 5.7 Multiplying Probabilities 61 Exercises [63] 6.4 Introduction to Statistical Hypothesis Testing [79] 6.5 Assessing Departures from Normality [86] Exercises [89] 7 ONE-SAMPLE HYPOTHESES [91] 7.1 Two-Tailed Hypotheses Concerning the Mean [91] 7.2 One-Tailed Hypotheses Concerning the Mean [96] 13 Confidence Limits for the Population Mean [98] 7.4 Reporting Variability about the Mean [100] 7.5 Sample Size and Estimation of the Population Mean [105] 7.6 Power and Sample Size in Tests Concerning the Mean [105] 7.7 Sampling Finite Populations [108] 7.8 Confidence Limits for the Population Median [110] 8 TWO-SAMPLE HYPOTHESES [122] 8.1 Testing for Difference between Two Means [122] 8.2 Confidence Limits for Population Means [129] 8.3 Sample Size and Estimation of the Difference between Two Population Means [131] 8.4 Power and Sample Size in Tests for Difference between Two Means [132] 8.5 Testing for Difference between Two Variances [136] 8.6 Confidence Interval for the Population Variance Ratio [139] 8.7 Sample Size and Power in Tests for Difference between Two Variances [140] 9 PAIRED-SAMPLE HYPOTHESES [161] 9.1 Testing Mean Difference [161] 9.2 Confidence Limits for the Population Mean Difference [164] 9.3 Power and Sample Size in Paired-Sample Testing of Means [164] 9.4 Testing for the Difference between Variances from Two Correlated Populations [164] 7.9 Hypotheses Concerning the Median [110] 7.10 Confidence Limits for the Population Variance [110] 7.11 Hypotheses Concerning the Variance [112] 7.12 Power and Sample Size in Tests Concerning the Variance [113] 7.13 Hypotheses Concerning the Coefficient of Variation [114] 7.14 Hypotheses Concerning Symmetry and Kurtosis [115] Exercises [120] 8.8 Testing for Difference between Two Coefficients of Variation [141] 8.9 Nonparametric Statistical Methods [145] 8.10 Two-Sample Rank Testing [146] 8.11 Testing for Difference between Two Medians [155] 8.12 The Effect of Coding [155] 8.13 Two-Sample Testing of Nominal-Scale Data [156] 8.14 Testing for Difference between Two Diversity Indices [156] Exercises [159] 9.5 Paired-Sample Testing by Ranks [165] 9.6 Confidence Limits for the Population Median Difference [169] 9.7 Paired-Sample Testing of Nominal-Scale Data [169] Exercises [175] 10 MULTISAMPLE HYPOTHESES: THE ANALYSIS OF VARIANCE [177] 10.1 Single-Factor Analysis of Variance [178] 10.2 Confidence Limits for Population Means [189] 10.3 Power and Sample Size in Analysis of Variance [189] 10.4 Nonparametric Analysis of Variance [195] 10.5 Testing for Difference among Several Medians [200] 10.6 Homogeneity of Variances [202] 10.7 Homogeneity of Coefficients of Variation [204] 10.8 The Effect of Coding [206] 10.9 Multisample Testing for Nominal-Scale Data [206] Exercises [206] 11 MULTIPLE COMPARISONS [208] 11.1 The Tukey Test [210] 11.2 The Newman-Keuls Test [214] 11.3 Confidence Intervals Following Multiple Comparisons [215] 114 Comparison of a Control Mean to Each Other Group Mean [217] 11.5 Scheffé's Multiple Contrasts [219] 11.6 Nonparametric Multiple Comparisons [223] 11.7 Nonparametric Multiple Contrasts [226] 11.8 Multiple Comparisons among Medians [226] 11.9 Multiple Comparisons among Variances [228] Exercises [230] 12 TWO-FACTOR ANALYSIS OF VARIANCE [231] 12.1 Two-Factor Analysis of Variance with Equal Replication [232] 12.2 Two-Factor Analysis of Variance with Unequal Replication [245] 12.3 Two-Factor Analysis of Variance without Replication [248] 12.4 The Randomized Block Experimental Design [250] 12.5 Repeated-Measures Experimental Designs [255] 12.6 Multiple Comparisons and Confidence Intervals in Two-Factor Analysis of Variance [260] 12.7 Power and Sample Size in Two-Factor Analysis of Variance [261] 12.8 Nonparametric Randomized Block or Repeated-Measures Analysis of Variance [263] 12.9 Multiple Comparisons for Nonparametric Randomized Block or Repeated-Measures Analysis of Variance [267] 12.10 Dichotomous Nominal-Scale Data in Randomized Blocks or from Repeated Measures [268] 12.11 Multiple Comparisons with Dichotomous Randomized Block or Repeated-Measures Data [270] 12.12 Introduction to Analysis of Covariance [270] Exercises [271] 13 DATA TRANSFORMATIONS [273] 13.1 The Logarithmic Transformation [275] 13.2 The Square Root Transformation [275] 133 The Arcsine Transformation [278] 13.4 Other Transformations [280] Exercises [280] 14 MULTIWAY FACTORIAL ANALYSIS OF VARIANCE [282] 14.1 Three-Factor Analysis of Variance [283] 14.2 The Latin Square Experimental Design [286] 14.3 Higher-Order Factorial Analysis of Variance [287] 14.4 Blocked and Repeated-Measures Experimental Designs [288] 14.5 Factorial Analysis of Variance with Unequal Replication [298] 14.6 Multiple Comparisons and Confidence Intervals in Multiway Analysis of Variance [299] 14.7 Power and Sample Size in Multiway Analysis of Variance [300] Exercises [300] 15 NESTED (HIERARCHICAL) ANALYSIS OF VARIANCE [303] 15.1 Nesting within One Main Factor [305] 15.2 Nesting in Factorial Experiments [308] 15.3 Multiple Comparisons and Confidence Intervals [310] 15.4 Power and Sample Size in Nested Analysis of Variance [311] Exercise [311] 16 MULTIVARIATE ANALYSIS OF VARIANCE [312] 16.1 The Multivariate Normal Distribution [313] 16.2 Multivariate Analysis of Variance Hypothesis Testing [316] 17 SIMPLE LINEAR REGRESSION [324] 17.1 Regression vs. Correlation [324] 17.2 The Simple Linear Regression Equation [326] 17.3 Testing the Significance of a Regression [333] 17.4 Confidence Intervals in Regression [337] 17.5 Inverse Prediction [342] 17.6 Interpretations of Regression Functions [344] 17.7 Regression with Replication and Testing for Linearity [345] 16.3 Further Analysis [322] 16.4 Other Experimental Designs [322] Exercises [323] 17.8 Power and Sample Size in Regression [350] 17.9 Regression through the Origin [351] 17.10 Data Transformations in Regression [353] 17.11 The Effect of Coding 357 Exercises [358] 18 COMPARING SIMPLE LINEAR REGRESSION EQUATIONS [360] 18.1 Comparing Two Slopes [360] 18.2 Comparing Two Elevations [364] 18.3 Comparing Points on Two Regression Lines [368] 18.4 Comparing more than Two Slopes [369] 18.5 Comparing more than Two Elevations [372] 18.6 Multiple Comparisons among Slopes [372] Multiple Comparisons among Elevations [373] Multiple Comparisons of Points among Regression Lines [374] An Overall Test for Coincidental Regressions [375] Exercises [375] 19 SIMPLE LINEAR CORRELATION [377] 19.1 The Correlation Coefficient [377] 19.2 Hypotheses about the Correlation Coefficient [381] 19.3 Confidence Intervals for the Population Correlation Coefficient [383] 19.4 Power and Sample Size in Correlation [385] 19.5 Comparing Two Correlation Coefficients [386] 19.6 Power and Sample Size in Comparing Two Correlation Coefficients [388] 19.7 Comparing more than Two Correlation Coefficients [390] 19.8 Multiple Comparisons among Correlation Coefficients [392] 19.9 Rank Correlation [395] 19.10 Weighted Rank Correlation [398] 19.11 Correlation for Dichotomous Nominal-Scale Data [401] 19.12 Intraclass Correlation [404] 19.13 Concordance Correlation [407] 19.14 The Effect of Coding [410] Exercises [410]
20 MULTIPLE REGRESSION AND CORRELATION [413] 20.1 Intermediate Computational Steps [414] 20.2 The Multiple Regression Equation [419] 20.3 Analysis of Variance of Multiple Regression or Correlation [422] 20.4 Hypotheses Concerning Partial Regression Coefficients [424] 20.5 Standardized Partial Regression Coefficients [426] 20.6 Partial Correlation [426] 20.7 Round-off Error and Coding Data [428] 20.8 Selection of Independent Variables [429] 20.9 Predicting Y Values [433] 20.10 Testing Difference between Two Partial Regression Coefficients [436] 20.11 “Dummy” Variables [436] 20.12 Interaction of Independent Variables [437] 20.13 Comparing Multiple Regression Equations [437] 20.14 Multiple Regression through the Origin [440] 20.15 Nonlinear Regression [440] 20.16 Descriptive vs. Predictive Models [442] 20.17 Concordance: Rank Correlation among Several Variables [443] Exercises [450] 21 POLYNOMIAL REGRESSION [452] 21.1 Polynomial Curve Fitting [452] 21.2 Round-off Error and Coding Data [457] 21.3 Quadratic Regression [457] Exercises [459] 22 TESTING FOR GOODNESS OF FIT [461] 22.1 Chi-Square Goodness of Fit [462] 22.2 Chi-Square Goodness of Fit for More than Two Categories [464] 22.3 Subdividing Chi-Square Analyses [466] 22.4 Chi-Square Correction for Continuity [468] 22.5 Bias in Chi-Square Calculations [470] 22.6 Heterogeneity Chi-Square [471] 22.7 The Log-Likelihood Ratio [473] 22.8 Kolmogorov-Smirnov Goodness of Fit for Discrete Data [475] 22.9 Kolmogorov-Smirnov Goodness of Fit for Continuous Data [478] 22.10 Sample Size Required for Kolmogorov-Smirnov Goodness of Fit for Continuous Data [481] Exercises [483] 23 CONTINGENCY TABLES [486] 23.1 Chi-Square Analysis of Contingency Tablds [488] 23.2 Graphing Contingency Table Data [490] 23.3 The 2x2 Contingency Table [491] 23.4 Heterogeneity Testing of 2 x 2 Tables [500] 23.5 Subdividing Contingency Tables [502] 23.6 Bias ih Chi-Square Contingency Table Analyses [504] 24 MORE ON DICHOTOMOUS VARIABLES [516] 24.1 Binomial Probabilities [517] 24.2 The Hypergeometric Distribution [523] 24.3 Sampling a Binomial Population [524] 24.4 Confidence Limits for Population Proportions [527] 24.5 Goodness of Fit for the Binomial Distribution [530] 24.6 The Binomial Test [533] 24.7 The Sign Test [538] 24.8 Power of the Binomial and Sign Tests [539] 25 TESTING FOR RANDOMNESS [571] 25.1 Poisson Probabilities [571] 25.2 Confidence Limits for the Poisson Parameter [574] 25.3 Goodness of Fit of the Poisson Distribution [575] 25.4 The Binomial Test Revisited [578] 25.5 Comparing Two Poisson Counts [582] 25.6 Serial Randomness of Nominal-Scale Categories [583] 23.7 The Log-Likelihood Ratio for Contingency Tables [505] 23.8 Three-Dimensional Contingency Tables [506] 23.9 Log-Linear Models for Multidimensional Contingency Tables [512] Exercises [514] 24.9 Confidence Interval for the Population Median [542] 24.10 The Fisher Exact Test [543] 24.11 Comparing Two Proportions [555] 24.12 Power and Sample Size in Comparing Two Proportions [558] 24.13 Comparing more than Two Proportions [562] 24.14 Multiple Comparisons for Proportions [563] 24.15 Trends among Proportions [565] Exercises [568] 25.7 Serial Randomness of Measurements: Parametric Testing [586] 25.8 Serial Randomness of Measurements: Nonparametric Testing [587] Exercises [590] 26 CIRCULAR DISTRIBUTIONS: DESCRIPTIVE STATISTICS [592] 26.1 Data on a Circular Scale [592] 26.2 Graphical Presentation of Circular Data [595] 26.3 Sines and Cosines of Circular Data [597] 26.4 The Mean Angle [599] 26.5 Angular Dispersion [602] 26.6 The Median and Modal Angles [605] 26.7 Confidence Limits for the Population Mean and Median Angles [605] 26.8 Diametrically Bimodal Distributions [607] 26.9 Second-Order Analysis: The Mean of Mean Angles [608] 26.10 Confidence Limits for the Second-Order Mean Angle [611] Exercises [614] 27 CIRCULAR DISTRIBUTIONS: HYPOTHESIS TESTING [616] [27.6] 27.1 Testing Significance of the Mean Angle: Unimodal Distributions [616] 27.2 Testing Significance of the Median Angle: Omnibus Test [621] 27.3 Testing Significance of the Median Angle: Binomial Test [624] 27.4 Testing Symmetry around the Median Angle [624] 27.5 Two-Sample and Multisample Testing of Mean Angles [625] Nonparametric Two-Sample and Multisample Testing of Angles [630] 27.7 Two-Sample and Multisample Testing of Median Angles [635] 27.8 Two-Sample and Multisample Testing of Angular Distances [635] 27.9 Two-Sample and Multisample Testing of Angular Dispersion [637] 27.10 Parametric One-Sample Second-Order Analysis of Angles [638] 27 CIRCULAR DISTRIBUTIONS: HYPOTHESIS TESTING (continued) 27.11 Nonparametric One-Sample Second-Order Analysis of Angles [639] 27.12 Parametric Two-Sample Second-Order Analysis of Angles [641] 27.13 Nonparametric Two-Sample Second-Order Analysis of Angles [643] 27.14 Parametric Paired-Sample Testing with Angles [645] 27.15 Nonparametric Paired-Sample Testing with Angles [647] 27.16 Parametric Angular Correlation and Regression [649] 27.17 Nonparametric Angular Correlation [653] 27.18 Goodness of Fit Testing for Circular Distributions [654] 27.19 Serial Randomness of Nominal-Scale Categories on a Circle [658] Exercises [660] APPENDIX A ANALYSIS OF VARIANCE HYPOTHESIS TESTING Appt A.1 Determination of Appropriate F’s and Degrees of Freedom Appl A.2 Two-Factor Analysis of Variance App5 A.3 Three-Factor Analysis of Variance App6 A.4 Nested Analysis of Variance App7 A.5 Split-Plot and Mixed Within-Subjects Analysis of Variance App8 APPENDIX B STATISTICAL TABLES AND GRAPHS App11 Table B.l Critical Values of Chi-Square Distribution Appl2 Table B.2 Proportions of the Normal Curve (One-Tailed) Appl7 Table B.3 Critical Values of the t Distribution Appl9 Table B.4 Critical Values of the F Distribution App21 Table B.5 Critical Values of the q Distribution App58 Table B.6 Critical Values of q' for the One-Tailed Dunnett’s Test App74 Table B.7 Critical Values of q' for the Two-Tailed Dunnett’s Test App76 Table B.8 Critical Values of dmax for the Kolmogorov-Smirnov Goodness of Fit Test for Discrete or Grouped Data App77 Table B.9 Critical Values of D for the Kolmogorov-Smirnov Goodness of Fit Test for Continuous Distributions App83 Table B.10 Critical Values of D§ for the 5-Corrected Kolmogorov-Smirnov Goodness of Fit Test for Continuous Distributions App87 Table B.ll Critical Values of the Mann-Whitney U Distribution App89 Table B.12 Critical Values of the Wilcoxon T Distribution ApplOl Table B.13 Critical Values of the Kruskal-Wallis H Distribution Appl04 Table B.14 Critical Values of the Friedman Xr Distribution Appl06 Table B.15 Critical Values of Q for Nonparametric Multiple Comparison Testing Appl07 Table B.16 Critical Values of Q' for Nonparametric Multiple Comparison Testing with a Control Appl08 Table B.17 Critical Values of the Correlation Coefficient, r Appl09 Table B.18 Fisher’s z Transformation for Correlation Coefficients, r Appl [11] Table B.19 Correlation Coefficients, r, Corresponding to Fisher’s z Transformation Appl [13] Table B.20 Critical Values of the Spearman Rank Correlation Coefficient, rs Appl [16] Table B.21 Critical Values of the Top-Down Correlation Coefficient, rT Appl [18] Table B.22 Critical Values of the Symmetry Measure, g1 Appl [19] Table B.23 Critical Values of the Kurtosis Measure, 82 Appl21 Table B.24 The Arcsine Transformation, p' Appl24 Table B.25 Proportions, p, Corresponding to Arcsine Transformations, p' Appl27 Table B.26a Binomial Coefficients, n Cx Appl29 Table B.26b Proportions of the Binomial Distribution for p = q = 0.5 Appl32 Table B.27 Critical Values of C for the Sign Test or for the Binomial Test with p = 0.5 Appl33 Table B.28 Critical Values for Fisher’s Exact Test Appl43 Table B.29 Critical Values for Runs Test Appl71 Table B.30 Critical Values of C for the Mean Square Successive Difference Test Appl80 Table B.31 Critical Values for the Runs Up and Down Test Appl82 APPENDIX B STATISTICAL TABLES AND GRAPHS (continued) Table B.32 Angular Deviation, s, As a Function of Vector Length, r Appl84 Table B.33 Circular Standard Deviation, so, As a Function of Vector Length, r Appl86 Table B.34 Critical Values of Rayleigh’s z Appl88 Table B.35 Critical Values of u for the V Test of Circular Uniformity Appl90 Table B.36 Critical Values of m for the Hodges-Ajne Test Appl91 Table B.37 Correction Factor, K, for the Watson and Williams Test Appl93 Table B.38 Critical Values of Watson’s I/2 Appl95 Table B.39 Critical Values of R' for the Moore Test of Circular Uniformity Appl98 Table B.40 Common Logarithms of Factorials Appl99 Table B.41 Ten Thousand Random Digits App201 Figure B.l Power and Sample Size in Analysis of Variance App205 ANSWERS TO EXERCISES Ansi LITERATURE CITED L1 INDEX [11]
| Item type | Home library | Shelving location | Call number | Materials specified | Status | Date due | Barcode | Course reserves |
|---|---|---|---|---|---|---|---|---|
Libros
|
Instituto de Matemática, CONICET-UNS | Libros ordenados por tema | 62 Z36-4 (Browse shelf) | Available | A-8061 |
Browsing Instituto de Matemática, CONICET-UNS shelves, Shelving location: Libros ordenados por tema Close shelf browser
Incluye referencias bibligráficas e índice.
1 INTRODUCTION [1] --
1.1 Types of Biological Data [2] --
1.2 Accuracy and Significant Figures [5] --
2 POPULATIONS AND SAMPLES [16] --
2.1 Populations [16] --
2.2 Samples from Populations [17] --
3 MEASURES OF CENTRAL TENDENCY [20] --
3.1 The Arithmetic Mean [20] --
3.2 The Median [23] --
3.3 Other Quantiles [26] --
3.4 The Mode [27] --
4 MEASURES OF DISPERSION AND VARIABILITY [32] --
4.1 The Range [32] --
4.2 Dispersion Measured with Quantiles [34] --
4.3 The Mean Deviation [34] --
4.4 The Variance [35] --
4.5 The Standard Deviation [39] --
5 PROBABILITIES [48] --
5.1 Counting Possible Outcomes [49] --
5.2 Permutations [50] --
5.3 Combinations [54] --
SA Sets [56] --
6 THE NORMAL DISTRIBUTION [65] --
6.1 Symmetry and Kurtosis [67] --
6.2 Proportions of a Normal Distribution [72] --
6.3 The Distribution of Means [76] --
1.3 Frequency Distributions [6] --
1.4 Cumulative Frequency Distributions [13] --
2.3 Random Sampling [17] --
2.4 Parameters and Statistics [18] --
3.5 Other Measures of Central Tendency [28] --
3.6 The Effect of Coding Data [29] --
Exercises [31] --
The Coefficient of Variation [40] --
Indices of Diversity [40] --
The Effect of Coding Data [44] --
Exercises [47] --
5.5 Probability of an Event [58] --
5.6 Adding Probabilities [59] --
5.7 Multiplying Probabilities 61 Exercises [63] --
6.4 Introduction to Statistical Hypothesis Testing [79] --
6.5 Assessing Departures from Normality [86] --
Exercises [89] --
7 ONE-SAMPLE HYPOTHESES [91] --
7.1 Two-Tailed Hypotheses Concerning the Mean [91] --
7.2 One-Tailed Hypotheses Concerning the Mean [96] --
13 Confidence Limits for the Population Mean [98] --
7.4 Reporting Variability about the Mean [100] --
7.5 Sample Size and Estimation of the Population Mean [105] --
7.6 Power and Sample Size in Tests Concerning the Mean [105] --
7.7 Sampling Finite Populations [108] --
7.8 Confidence Limits for the Population Median [110] --
8 TWO-SAMPLE HYPOTHESES [122] --
8.1 Testing for Difference between Two Means [122] --
8.2 Confidence Limits for Population Means [129] --
8.3 Sample Size and Estimation of the Difference between Two Population Means [131] --
8.4 Power and Sample Size in Tests for Difference between Two Means [132] --
8.5 Testing for Difference between Two Variances [136] --
8.6 Confidence Interval for the Population Variance Ratio [139] --
8.7 Sample Size and Power in Tests for Difference between Two Variances [140] --
9 PAIRED-SAMPLE HYPOTHESES [161] --
9.1 Testing Mean Difference [161] --
9.2 Confidence Limits for the Population Mean Difference [164] --
9.3 Power and Sample Size in Paired-Sample Testing of Means [164] --
9.4 Testing for the Difference between Variances from Two Correlated Populations [164] --
7.9 Hypotheses Concerning the Median [110] --
7.10 Confidence Limits for the Population Variance [110] --
7.11 Hypotheses Concerning the Variance [112] --
7.12 Power and Sample Size in Tests Concerning the Variance [113] --
7.13 Hypotheses Concerning the Coefficient of Variation [114] --
7.14 Hypotheses Concerning Symmetry and Kurtosis [115] --
Exercises [120] --
8.8 Testing for Difference between Two Coefficients of Variation [141] --
8.9 Nonparametric Statistical Methods [145] --
8.10 Two-Sample Rank Testing [146] --
8.11 Testing for Difference between Two Medians [155] --
8.12 The Effect of Coding [155] --
8.13 Two-Sample Testing of Nominal-Scale Data [156] --
8.14 Testing for Difference between Two Diversity Indices [156] --
Exercises [159] --
9.5 Paired-Sample Testing by Ranks [165] --
9.6 Confidence Limits for the Population Median Difference [169] --
9.7 Paired-Sample Testing of Nominal-Scale Data [169] --
Exercises [175] --
10 MULTISAMPLE HYPOTHESES: THE ANALYSIS OF VARIANCE [177] --
10.1 Single-Factor Analysis of Variance [178] --
10.2 Confidence Limits for Population Means [189] --
10.3 Power and Sample Size in Analysis of Variance [189] --
10.4 Nonparametric Analysis of Variance [195] --
10.5 Testing for Difference among Several Medians [200] --
10.6 Homogeneity of Variances [202] --
10.7 Homogeneity of Coefficients of Variation [204] --
10.8 The Effect of Coding [206] --
10.9 Multisample Testing for Nominal-Scale Data [206] --
Exercises [206] --
11 MULTIPLE COMPARISONS [208] --
11.1 The Tukey Test [210] --
11.2 The Newman-Keuls Test [214] --
11.3 Confidence Intervals Following Multiple Comparisons [215] --
114 Comparison of a Control Mean to Each Other Group Mean [217] --
11.5 Scheffé's Multiple Contrasts [219] --
11.6 Nonparametric Multiple Comparisons [223] --
11.7 Nonparametric Multiple Contrasts [226] --
11.8 Multiple Comparisons among Medians [226] --
11.9 Multiple Comparisons among Variances [228] --
Exercises [230] --
12 TWO-FACTOR ANALYSIS OF VARIANCE [231] --
12.1 Two-Factor Analysis of Variance with Equal Replication [232] --
12.2 Two-Factor Analysis of Variance with Unequal Replication [245] --
12.3 Two-Factor Analysis of Variance without Replication [248] --
12.4 The Randomized Block Experimental Design [250] --
12.5 Repeated-Measures Experimental Designs [255] --
12.6 Multiple Comparisons and Confidence Intervals in Two-Factor Analysis of Variance [260] --
12.7 Power and Sample Size in Two-Factor Analysis of Variance [261] --
12.8 Nonparametric Randomized Block or Repeated-Measures Analysis of Variance [263] --
12.9 Multiple Comparisons for Nonparametric Randomized Block or Repeated-Measures Analysis of Variance [267] --
12.10 Dichotomous Nominal-Scale Data in Randomized Blocks or from Repeated Measures [268] --
12.11 Multiple Comparisons with Dichotomous Randomized Block or Repeated-Measures Data [270] --
12.12 Introduction to Analysis of Covariance [270] --
Exercises [271] --
13 DATA TRANSFORMATIONS [273] --
13.1 The Logarithmic Transformation [275] --
13.2 The Square Root Transformation [275] --
133 The Arcsine Transformation [278] --
13.4 Other Transformations [280] --
Exercises [280] --
14 MULTIWAY FACTORIAL ANALYSIS OF VARIANCE [282] --
14.1 Three-Factor Analysis of Variance [283] --
14.2 The Latin Square Experimental Design [286] --
14.3 Higher-Order Factorial Analysis of Variance [287] --
14.4 Blocked and Repeated-Measures Experimental Designs [288] --
14.5 Factorial Analysis of Variance with Unequal Replication [298] --
14.6 Multiple Comparisons and Confidence Intervals in Multiway Analysis of Variance [299] --
14.7 Power and Sample Size in Multiway Analysis of Variance [300] --
Exercises [300] --
15 NESTED (HIERARCHICAL) ANALYSIS OF VARIANCE [303] --
15.1 Nesting within One Main Factor [305] --
15.2 Nesting in Factorial Experiments [308] --
15.3 Multiple Comparisons and Confidence Intervals [310] --
15.4 Power and Sample Size in Nested Analysis of Variance [311] --
Exercise [311] --
16 MULTIVARIATE ANALYSIS OF VARIANCE [312] --
16.1 The Multivariate Normal Distribution [313] --
16.2 Multivariate Analysis of Variance Hypothesis Testing [316] --
17 SIMPLE LINEAR REGRESSION [324] --
17.1 Regression vs. Correlation [324] --
17.2 The Simple Linear Regression Equation [326] --
17.3 Testing the Significance of a Regression [333] --
17.4 Confidence Intervals in Regression [337] --
17.5 Inverse Prediction [342] --
17.6 Interpretations of Regression Functions [344] --
17.7 Regression with Replication and Testing for Linearity [345] --
16.3 Further Analysis [322] --
16.4 Other Experimental Designs [322] --
Exercises [323] --
17.8 Power and Sample Size in Regression [350] --
17.9 Regression through the Origin [351] --
17.10 Data Transformations in Regression [353] --
17.11 The Effect of Coding 357 Exercises [358] --
18 COMPARING SIMPLE LINEAR REGRESSION EQUATIONS [360] --
18.1 Comparing Two Slopes [360] --
18.2 Comparing Two Elevations [364] --
18.3 Comparing Points on Two Regression Lines [368] --
18.4 Comparing more than Two Slopes [369] --
18.5 Comparing more than Two Elevations [372] --
18.6 Multiple Comparisons among Slopes [372] --
Multiple Comparisons among Elevations [373] --
Multiple Comparisons of Points among Regression Lines [374] --
An Overall Test for Coincidental Regressions [375] --
Exercises [375] --
19 SIMPLE LINEAR CORRELATION [377] --
19.1 The Correlation Coefficient [377] --
19.2 Hypotheses about the Correlation Coefficient [381] --
19.3 Confidence Intervals for the Population Correlation Coefficient [383] --
19.4 Power and Sample Size in Correlation [385] --
19.5 Comparing Two Correlation Coefficients [386] --
19.6 Power and Sample Size in Comparing Two Correlation Coefficients [388] --
19.7 Comparing more than Two Correlation Coefficients [390] --
19.8 Multiple Comparisons among Correlation Coefficients [392] --
19.9 Rank Correlation [395] --
19.10 Weighted Rank Correlation [398] --
19.11 Correlation for Dichotomous Nominal-Scale Data [401] --
19.12 Intraclass Correlation [404] --
19.13 Concordance Correlation [407] --
19.14 The Effect of Coding [410] --
Exercises [410] --
20 MULTIPLE REGRESSION AND CORRELATION [413] --
20.1 Intermediate Computational Steps [414] --
20.2 The Multiple Regression Equation [419] --
20.3 Analysis of Variance of Multiple Regression or Correlation [422] --
20.4 Hypotheses Concerning Partial Regression Coefficients [424] --
20.5 Standardized Partial Regression Coefficients [426] --
20.6 Partial Correlation [426] --
20.7 Round-off Error and Coding Data [428] --
20.8 Selection of Independent Variables [429] --
20.9 Predicting Y Values [433] --
20.10 Testing Difference between Two Partial --
Regression Coefficients [436] --
20.11 “Dummy” Variables [436] --
20.12 Interaction of Independent Variables [437] --
20.13 Comparing Multiple Regression Equations [437] --
20.14 Multiple Regression through the Origin [440] --
20.15 Nonlinear Regression [440] --
20.16 Descriptive vs. Predictive Models [442] --
20.17 Concordance: Rank Correlation among Several Variables [443] --
Exercises [450] --
21 POLYNOMIAL REGRESSION [452] --
21.1 Polynomial Curve Fitting [452] --
21.2 Round-off Error and Coding Data [457] --
21.3 Quadratic Regression [457] --
Exercises [459] --
22 TESTING FOR GOODNESS OF FIT [461] --
22.1 Chi-Square Goodness of Fit [462] --
22.2 Chi-Square Goodness of Fit for More than Two Categories [464] --
22.3 Subdividing Chi-Square Analyses [466] --
22.4 Chi-Square Correction for Continuity [468] --
22.5 Bias in Chi-Square Calculations [470] --
22.6 Heterogeneity Chi-Square [471] --
22.7 The Log-Likelihood Ratio [473] --
22.8 Kolmogorov-Smirnov Goodness of Fit for Discrete Data [475] --
22.9 Kolmogorov-Smirnov Goodness of Fit for Continuous Data [478] --
22.10 Sample Size Required for Kolmogorov-Smirnov Goodness of Fit for Continuous Data [481] --
Exercises [483] --
23 CONTINGENCY TABLES [486] --
23.1 Chi-Square Analysis of Contingency Tablds [488] --
23.2 Graphing Contingency Table Data [490] --
23.3 The 2x2 Contingency Table [491] --
23.4 Heterogeneity Testing of 2 x 2 Tables [500] --
23.5 Subdividing Contingency Tables [502] --
23.6 Bias ih Chi-Square Contingency Table Analyses [504] --
24 MORE ON DICHOTOMOUS VARIABLES [516] --
24.1 Binomial Probabilities [517] --
24.2 The Hypergeometric Distribution [523] --
24.3 Sampling a Binomial Population [524] --
24.4 Confidence Limits for Population Proportions [527] --
24.5 Goodness of Fit for the Binomial Distribution [530] --
24.6 The Binomial Test [533] --
24.7 The Sign Test [538] --
24.8 Power of the Binomial and Sign Tests [539] --
25 TESTING FOR RANDOMNESS [571] --
25.1 Poisson Probabilities [571] --
25.2 Confidence Limits for the Poisson Parameter [574] --
25.3 Goodness of Fit of the Poisson Distribution [575] --
25.4 The Binomial Test Revisited [578] --
25.5 Comparing Two Poisson Counts [582] --
25.6 Serial Randomness of Nominal-Scale Categories [583] --
23.7 The Log-Likelihood Ratio for Contingency Tables [505] --
23.8 Three-Dimensional Contingency Tables [506] --
23.9 Log-Linear Models for Multidimensional Contingency Tables [512] --
Exercises [514] --
24.9 Confidence Interval for the Population Median [542] --
24.10 The Fisher Exact Test [543] --
24.11 Comparing Two Proportions [555] --
24.12 Power and Sample Size in Comparing Two Proportions [558] --
24.13 Comparing more than Two Proportions [562] --
24.14 Multiple Comparisons for Proportions [563] --
24.15 Trends among Proportions [565] --
Exercises [568] --
25.7 Serial Randomness of Measurements: Parametric Testing [586] --
25.8 Serial Randomness of Measurements: Nonparametric Testing [587] --
Exercises [590] --
26 CIRCULAR DISTRIBUTIONS: DESCRIPTIVE STATISTICS [592] --
26.1 Data on a Circular Scale [592] --
26.2 Graphical Presentation of Circular Data [595] --
26.3 Sines and Cosines of Circular Data [597] --
26.4 The Mean Angle [599] --
26.5 Angular Dispersion [602] --
26.6 The Median and Modal Angles [605] --
26.7 Confidence Limits for the Population Mean and Median Angles [605] --
26.8 Diametrically Bimodal Distributions [607] --
26.9 Second-Order Analysis: The Mean of Mean Angles [608] --
26.10 Confidence Limits for the Second-Order Mean Angle [611] --
Exercises [614] --
27 CIRCULAR DISTRIBUTIONS: HYPOTHESIS TESTING [616] --
[27.6] --
27.1 Testing Significance of the Mean Angle: Unimodal Distributions [616] --
27.2 Testing Significance of the Median Angle: Omnibus Test [621] --
27.3 Testing Significance of the Median Angle: Binomial Test [624] --
27.4 Testing Symmetry around the Median Angle [624] --
27.5 Two-Sample and Multisample Testing of Mean Angles [625] --
Nonparametric Two-Sample and Multisample Testing of Angles [630] --
27.7 Two-Sample and Multisample Testing of Median Angles [635] --
27.8 Two-Sample and Multisample Testing of Angular Distances [635] --
27.9 Two-Sample and Multisample Testing of Angular Dispersion [637] --
27.10 Parametric One-Sample Second-Order Analysis of Angles [638] --
27 CIRCULAR DISTRIBUTIONS: HYPOTHESIS TESTING (continued) --
27.11 Nonparametric One-Sample Second-Order Analysis of Angles [639] --
27.12 Parametric Two-Sample Second-Order Analysis of Angles [641] --
27.13 Nonparametric Two-Sample Second-Order Analysis of Angles [643] --
27.14 Parametric Paired-Sample Testing with Angles [645] --
27.15 Nonparametric Paired-Sample Testing with Angles [647] --
27.16 Parametric Angular Correlation and Regression [649] --
27.17 Nonparametric Angular Correlation [653] --
27.18 Goodness of Fit Testing for Circular Distributions [654] --
27.19 Serial Randomness of Nominal-Scale Categories on a Circle [658] --
Exercises [660] --
APPENDIX A ANALYSIS OF VARIANCE HYPOTHESIS TESTING Appt --
A.1 Determination of Appropriate F’s and Degrees of Freedom Appl --
A.2 Two-Factor Analysis of Variance App5 --
A.3 Three-Factor Analysis of Variance App6 --
A.4 Nested Analysis of Variance App7 --
A.5 Split-Plot and Mixed Within-Subjects Analysis of Variance App8 --
APPENDIX B STATISTICAL TABLES AND GRAPHS App11 --
Table B.l Critical Values of Chi-Square Distribution Appl2 --
Table B.2 Proportions of the Normal Curve (One-Tailed) Appl7 --
Table B.3 Critical Values of the t Distribution Appl9 --
Table B.4 Critical Values of the F Distribution App21 --
Table B.5 Critical Values of the q Distribution App58 --
Table B.6 Critical Values of q' for the One-Tailed Dunnett’s Test App74 --
Table B.7 Critical Values of q' for the Two-Tailed Dunnett’s Test App76 --
Table B.8 Critical Values of dmax for the Kolmogorov-Smirnov Goodness of Fit Test for Discrete or Grouped Data App77 --
Table B.9 Critical Values of D for the Kolmogorov-Smirnov Goodness of Fit Test for Continuous Distributions App83 --
Table B.10 Critical Values of D§ for the 5-Corrected Kolmogorov-Smirnov Goodness of Fit Test for Continuous Distributions App87 --
Table B.ll Critical Values of the Mann-Whitney U Distribution App89 --
Table B.12 Critical Values of the Wilcoxon T Distribution ApplOl --
Table B.13 Critical Values of the Kruskal-Wallis H Distribution Appl04 --
Table B.14 Critical Values of the Friedman Xr Distribution Appl06 --
Table B.15 Critical Values of Q for Nonparametric Multiple Comparison Testing Appl07 --
Table B.16 Critical Values of Q' for Nonparametric Multiple Comparison Testing with a Control Appl08 --
Table B.17 Critical Values of the Correlation Coefficient, r Appl09 --
Table B.18 Fisher’s z Transformation for Correlation Coefficients, r Appl [11] --
Table B.19 Correlation Coefficients, r, Corresponding to Fisher’s z Transformation Appl [13] --
Table B.20 Critical Values of the Spearman Rank Correlation Coefficient, rs Appl [16] --
Table B.21 Critical Values of the Top-Down Correlation Coefficient, rT Appl [18] --
Table B.22 Critical Values of the Symmetry Measure, g1 Appl [19] --
Table B.23 Critical Values of the Kurtosis Measure, 82 Appl21 --
Table B.24 The Arcsine Transformation, p' Appl24 --
Table B.25 Proportions, p, Corresponding to Arcsine Transformations, p' Appl27 --
Table B.26a Binomial Coefficients, n Cx Appl29 --
Table B.26b Proportions of the Binomial Distribution for p = q = 0.5 Appl32 --
Table B.27 Critical Values of C for the Sign Test or for the Binomial Test with p = 0.5 Appl33 --
Table B.28 Critical Values for Fisher’s Exact --
Test Appl43 --
Table B.29 Critical Values for Runs Test Appl71 --
Table B.30 Critical Values of C for the Mean Square Successive Difference Test Appl80 --
Table B.31 Critical Values for the Runs Up and Down Test Appl82 --
APPENDIX B STATISTICAL TABLES AND GRAPHS (continued) --
Table B.32 Angular Deviation, s, As a Function of Vector Length, r Appl84 --
Table B.33 Circular Standard Deviation, so, As a Function of Vector Length, r Appl86 --
Table B.34 Critical Values of Rayleigh’s z Appl88 --
Table B.35 Critical Values of u for the V Test of Circular Uniformity Appl90 --
Table B.36 Critical Values of m for the Hodges-Ajne Test Appl91 --
Table B.37 Correction Factor, K, for the Watson and Williams Test Appl93 --
Table B.38 Critical Values of Watson’s I/2 Appl95 --
Table B.39 Critical Values of R' for the Moore Test of Circular Uniformity Appl98 --
Table B.40 Common Logarithms of Factorials Appl99 --
Table B.41 Ten Thousand Random Digits App201 Figure B.l Power and Sample Size in Analysis of Variance App205 --
ANSWERS TO EXERCISES Ansi --
LITERATURE CITED L1 --
INDEX [11] --
MR, REVIEW #
Click on an image to view it in the image viewer
There are no comments on this title.