{"product_id":"biostatistics-decoded-isbn-9781119584209","title":"Biostatistics Decoded","description":"\u003cp\u003e\u003ci\u003eBiostatistics Decoded\u003c\/i\u003e covered a large number of statistical methods that are mainly applied to clinical and epidemiological research, as well as a comprehensive discussion of study designs for observational research and clinical trials, two important concerns for the clinical researcher.\u003c\/p\u003e \u003cp\u003eIn this second edition, new material is included covering statistical methods and study designs that are used to analyse research. Following the same methodology used in the first edition, the chapters are presented in two levels of detail, one for the reader who wishes only to understand the rationale behind each statistical method, and one for the reader who wishes to understand the computations\u003c\/p\u003e \u003cp\u003eKey features include:\u003c\/p\u003e \u003cul\u003e \u003cli\u003eExtensive coverage of the design and analysis of experiments for basic science research\u003c\/li\u003e \u003cli\u003eExperimental designs are presented together with the statistical methods\u003c\/li\u003e \u003cli\u003eThe rationale of all forms of ANOVA is explained with simple mathematics\u003c\/li\u003e \u003cli\u003eA comprehensive presentation of statistical tests for multiple comparisons\u003c\/li\u003e \u003cli\u003eCalculations for all statistical methods are illustrated with examples and explained step-by-step.\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eThis book presents biostatistical concepts and methods in a way that is accessible to anyone, regardless of his or her knowledge of mathematics. The topics selected for this book cover will meet the needs of clinical professionals to readers in basic science research.\u003c\/p\u003e \u003cp\u003ePreface xi\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Populations and Samples \u003c\/b\u003e\u003cb\u003e1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1 The Object of Biostatistics 1\u003c\/p\u003e \u003cp\u003e1.2 Scales of Measurement 3\u003c\/p\u003e \u003cp\u003e1.3 Central Tendency Measures 5\u003c\/p\u003e \u003cp\u003e1.4 Sampling 8\u003c\/p\u003e \u003cp\u003e1.5 Inferences from Samples 11\u003c\/p\u003e \u003cp\u003e1.6 Measures of Location and Dispersion 14\u003c\/p\u003e \u003cp\u003e1.7 The Standard Deviation 15\u003c\/p\u003e \u003cp\u003e1.8 The \u003ci\u003en \u003c\/i\u003e− 1 Divisor 16\u003c\/p\u003e \u003cp\u003e1.9 Degrees of Freedom 18\u003c\/p\u003e \u003cp\u003e1.10 Variance of Binary Variables 19\u003c\/p\u003e \u003cp\u003e1.11 Properties of Means and Variances 20\u003c\/p\u003e \u003cp\u003e1.12 Descriptive Statistics 22\u003c\/p\u003e \u003cp\u003e1.13 Sampling Variation 25\u003c\/p\u003e \u003cp\u003e1.14 The Normal Distribution 27\u003c\/p\u003e \u003cp\u003e1.15 The Central Limit Theorem 29\u003c\/p\u003e \u003cp\u003e1.16 Properties of the Normal Distribution 30\u003c\/p\u003e \u003cp\u003e1.17 Probability Distribution of Sample Means 32\u003c\/p\u003e \u003cp\u003e1.18 The Standard Error of the Mean 33\u003c\/p\u003e \u003cp\u003e1.19 The Value of the Standard Error 35\u003c\/p\u003e \u003cp\u003e1.20 Distribution of Sample Proportions 37\u003c\/p\u003e \u003cp\u003e1.21 Convergence of Binomial to Normal Distribution 39\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Descriptive Studies \u003c\/b\u003e\u003cb\u003e41\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1 Designing a Research 41\u003c\/p\u003e \u003cp\u003e2.2 Study Design 42\u003c\/p\u003e \u003cp\u003e2.3 Classification of Descriptive Studies 44\u003c\/p\u003e \u003cp\u003e2.4 Cross-sectional Studies 45\u003c\/p\u003e \u003cp\u003e2.5 Inferences from Means 47\u003c\/p\u003e \u003cp\u003e2.6 Confidence Intervals 48\u003c\/p\u003e \u003cp\u003e2.7 Statistical Tables 49\u003c\/p\u003e \u003cp\u003e2.8 The Case of Small Samples 51\u003c\/p\u003e \u003cp\u003e2.9 Student’s \u003ci\u003et \u003c\/i\u003eDistribution 54\u003c\/p\u003e \u003cp\u003e2.10 Statistical Tables of the \u003ci\u003et \u003c\/i\u003eDistribution 56\u003c\/p\u003e \u003cp\u003e2.11 Inferences from Proportions 58\u003c\/p\u003e \u003cp\u003e2.12 Statistical Tables of the Binomial Distribution 60\u003c\/p\u003e \u003cp\u003e2.13 Sample Size Requirements 61\u003c\/p\u003e \u003cp\u003e2.14 Longitudinal Studies 63\u003c\/p\u003e \u003cp\u003e2.15 Incidence Studies 65\u003c\/p\u003e \u003cp\u003e2.16 Cohort Studies 66\u003c\/p\u003e \u003cp\u003e2.17 Inference from Incidence Studies 70\u003c\/p\u003e \u003cp\u003e2.18 Standardization 72\u003c\/p\u003e \u003cp\u003e2.19 Time-to-Event Cohort Studies 75\u003c\/p\u003e \u003cp\u003e2.20 The Actuarial Method 76\u003c\/p\u003e \u003cp\u003e2.21 The Kaplan–Meier Method 79\u003c\/p\u003e \u003cp\u003e2.22 Probability Sampling 82\u003c\/p\u003e \u003cp\u003e2.23 Simple Random Sampling 84\u003c\/p\u003e \u003cp\u003e2.24 Replacement in Sampling 85\u003c\/p\u003e \u003cp\u003e2.25 Stratified Sampling 87\u003c\/p\u003e \u003cp\u003e2.26 Multistage Sampling 92\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Analytical Studies \u003c\/b\u003e\u003cb\u003e97\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1 Objectives of Analytical Studies 97\u003c\/p\u003e \u003cp\u003e3.2 Measures of Association 98\u003c\/p\u003e \u003cp\u003e3.3 Odds, Logits, and Odds Ratios 99\u003c\/p\u003e \u003cp\u003e3.4 Attributable Risk 101\u003c\/p\u003e \u003cp\u003e3.5 Classification of Analytical Studies 103\u003c\/p\u003e \u003cp\u003e3.6 Uncontrolled Analytical Studies 104\u003c\/p\u003e \u003cp\u003e3.7 Comparative Analytical Studies 105\u003c\/p\u003e \u003cp\u003e3.8 Hybrid Analytical Studies 109\u003c\/p\u003e \u003cp\u003e3.9 Non-probability Sampling in Analytical Studies 111\u003c\/p\u003e \u003cp\u003e3.10 Comparison of Two Means 111\u003c\/p\u003e \u003cp\u003e3.11 Comparison of Two Means from Small Samples 114\u003c\/p\u003e \u003cp\u003e3.12 Comparison of Two Proportions 116\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Statistical Tests \u003c\/b\u003e\u003cb\u003e121\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1 The Null and Alternative Hypotheses 121\u003c\/p\u003e \u003cp\u003e4.2 The \u003ci\u003ez\u003c\/i\u003e-Test 122\u003c\/p\u003e \u003cp\u003e4.3 The \u003ci\u003ep\u003c\/i\u003e-Value 125\u003c\/p\u003e \u003cp\u003e4.4 Student’s \u003ci\u003et\u003c\/i\u003e-Test 126\u003c\/p\u003e \u003cp\u003e4.5 The Binomial Test 128\u003c\/p\u003e \u003cp\u003e4.6 The Chi-Square Test 130\u003c\/p\u003e \u003cp\u003e4.7 The Table of the Chi-Square Distribution 134\u003c\/p\u003e \u003cp\u003e4.8 Analysis of Variance 135\u003c\/p\u003e \u003cp\u003e4.9 Partitioning the Sum of Squares 139\u003c\/p\u003e \u003cp\u003e4.10 Statistical Tables of the \u003ci\u003eF \u003c\/i\u003eDistribution 142\u003c\/p\u003e \u003cp\u003e4.11 The ANOVA Table 143\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Aspects of Statistical Tests \u003c\/b\u003e\u003cb\u003e145\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1 One-Sided Tests 145\u003c\/p\u003e \u003cp\u003e5.2 Power of a Statistical Test 149\u003c\/p\u003e \u003cp\u003e5.3 Sample Size Estimation 150\u003c\/p\u003e \u003cp\u003e5.4 Multiple Comparisons 153\u003c\/p\u003e \u003cp\u003e5.5 Scale Transformation 155\u003c\/p\u003e \u003cp\u003e5.6 Non-parametric Tests 156\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Cross-sectional Studies \u003c\/b\u003e\u003cb\u003e161\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.1 Linear Regression 161\u003c\/p\u003e \u003cp\u003e6.2 The Least Squares Method 163\u003c\/p\u003e \u003cp\u003e6.3 Linear Regression Estimates 166\u003c\/p\u003e \u003cp\u003e6.4 Regression and Correlation 171\u003c\/p\u003e \u003cp\u003e6.5 The \u003ci\u003eF\u003c\/i\u003e-Test in Linear Regression 173\u003c\/p\u003e \u003cp\u003e6.6 Interpretation of Regression Analysis Results 176\u003c\/p\u003e \u003cp\u003e6.7 Multiple Regression 177\u003c\/p\u003e \u003cp\u003e6.8 Regression Diagnostics 180\u003c\/p\u003e \u003cp\u003e6.9 Selection of Predictor Variables 184\u003c\/p\u003e \u003cp\u003e6.10 Independent Nominal Variables 185\u003c\/p\u003e \u003cp\u003e6.11 Interaction 188\u003c\/p\u003e \u003cp\u003e6.12 Nonlinear Regression 190\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Case–Control Studies \u003c\/b\u003e\u003cb\u003e193\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7.1 Analysis of Case–Control Studies 193\u003c\/p\u003e \u003cp\u003e7.2 Logistic Regression 194\u003c\/p\u003e \u003cp\u003e7.3 The Method of Maximum Likelihood 196\u003c\/p\u003e \u003cp\u003e7.4 Estimation of the Logistic Regression Model 198\u003c\/p\u003e \u003cp\u003e7.5 The Likelihood Ratio Test 201\u003c\/p\u003e \u003cp\u003e7.6 Interpreting the Results of Logistic Regression 202\u003c\/p\u003e \u003cp\u003e7.7 Regression Coefficients and Odds Ratios 203\u003c\/p\u003e \u003cp\u003e7.8 Applications of Logistic Regression 204\u003c\/p\u003e \u003cp\u003e7.9 The ROC Curve 205\u003c\/p\u003e \u003cp\u003e7.10 Model Validation 208\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Cohort Studies \u003c\/b\u003e\u003cb\u003e213\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8.1 Repeated Measurements 213\u003c\/p\u003e \u003cp\u003e8.2 The Paired \u003ci\u003et\u003c\/i\u003e-Test 213\u003c\/p\u003e \u003cp\u003e8.3 McNemar’s Test 215\u003c\/p\u003e \u003cp\u003e8.4 Generalized Linear Models 216\u003c\/p\u003e \u003cp\u003e8.5 The Logrank Test 219\u003c\/p\u003e \u003cp\u003e8.6 The Adjusted Logrank Test 222\u003c\/p\u003e \u003cp\u003e8.7 The Incidence Rate Ratio 224\u003c\/p\u003e \u003cp\u003e8.8 The Cox Proportional Hazards Model 225\u003c\/p\u003e \u003cp\u003e8.9 Assumptions of the Cox Model 229\u003c\/p\u003e \u003cp\u003e8.10 Interpretation of Cox Regression 230\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Measurement \u003c\/b\u003e\u003cb\u003e233\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e9.1 Construction of Clinical Questionnaires 233\u003c\/p\u003e \u003cp\u003e9.2 Factor Analysis 234\u003c\/p\u003e \u003cp\u003e9.3 Interpretation of Factor Analysis 237\u003c\/p\u003e \u003cp\u003e9.4 Factor Rotation 239\u003c\/p\u003e \u003cp\u003e9.5 Factor Scores 241\u003c\/p\u003e \u003cp\u003e9.6 Reliability 242\u003c\/p\u003e \u003cp\u003e9.7 Concordance 248\u003c\/p\u003e \u003cp\u003e9.8 Validity 253\u003c\/p\u003e \u003cp\u003e9.9 Validation of Diagnostic Tests 255\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Experimental Studies \u003c\/b\u003e\u003cb\u003e257\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e10.1 Main Design Features and Classification 257\u003c\/p\u003e \u003cp\u003e10.2 Experimental Controls 260\u003c\/p\u003e \u003cp\u003e10.3 Replicates 261\u003c\/p\u003e \u003cp\u003e10.4 Classification of Experimental Designs 262\u003c\/p\u003e \u003cp\u003e10.5 Completely Randomized Design 263\u003c\/p\u003e \u003cp\u003e10.6 Interaction 268\u003c\/p\u003e \u003cp\u003e10.7 Full Factorial Design 269\u003c\/p\u003e \u003cp\u003e10.8 The Random Effects Model 274\u003c\/p\u003e \u003cp\u003e10.9 Components of Variance 275\u003c\/p\u003e \u003cp\u003e10.10 ANOVA Model II and Model III 278\u003c\/p\u003e \u003cp\u003e10.11 Rules for the Definition of the Error Terms 282\u003c\/p\u003e \u003cp\u003e10.12 ANOVA on Ranks 284\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Blocking \u003c\/b\u003e\u003cb\u003e285\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e11.1 Randomized Block Design 285\u003c\/p\u003e \u003cp\u003e11.2 Generalized Randomized Block Design 288\u003c\/p\u003e \u003cp\u003e11.3 Incomplete Block Design 291\u003c\/p\u003e \u003cp\u003e11.4 Factorial Design with Randomized Blocks 292\u003c\/p\u003e \u003cp\u003e11.5 Latin and Greco-Latin Square Design 293\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 Simultaneous Inference \u003c\/b\u003e\u003cb\u003e297\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e12.1 Multiple Comparisons 297\u003c\/p\u003e \u003cp\u003e12.2 Generalist Methods 298\u003c\/p\u003e \u003cp\u003e12.3 Multiple Comparisons of Group Means 303\u003c\/p\u003e \u003cp\u003e12.4 Pairwise Comparison of Means 304\u003c\/p\u003e \u003cp\u003e12.5 Different Variances 312\u003c\/p\u003e \u003cp\u003e12.6 Comparison to a Control 313\u003c\/p\u003e \u003cp\u003e12.7 Comparison of \u003ci\u003epost hoc \u003c\/i\u003eTests 315\u003c\/p\u003e \u003cp\u003e12.8 Complex Comparisons 316\u003c\/p\u003e \u003cp\u003e12.9 Tests of Multiple Contrasts 320\u003c\/p\u003e \u003cp\u003e12.10 \u003ci\u003eA posteriori \u003c\/i\u003eContrasts 324\u003c\/p\u003e \u003cp\u003e12.11 The Size of an Experiment 326\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13 Factorial ANOVA \u003c\/b\u003e\u003cb\u003e329\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e13.1 The \u003ci\u003en\u003c\/i\u003e-Way ANOVA 329\u003c\/p\u003e \u003cp\u003e13.2 The 2\u003ci\u003e\u003csup\u003ek\u003c\/sup\u003e \u003c\/i\u003eFactorial Design 331\u003c\/p\u003e \u003cp\u003e13.3 The 2\u003ci\u003e\u003csup\u003ek\u003c\/sup\u003e \u003c\/i\u003eFactorial Design with Blocking 335\u003c\/p\u003e \u003cp\u003e13.4 The Fractional Factorial Design 337\u003c\/p\u003e \u003cp\u003e\u003cb\u003e14 Nested Designs \u003c\/b\u003e\u003cb\u003e339\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e14.1 Split–Plot Design 339\u003c\/p\u003e \u003cp\u003e14.2 Nested (Hierarchical) Design 343\u003c\/p\u003e \u003cp\u003e14.3 Mixed Model Nested ANOVA 345\u003c\/p\u003e \u003cp\u003e14.4 Mixed Model Nested ANOVA with Three Sublevels 349\u003c\/p\u003e \u003cp\u003e14.5 Pure Model II Nested ANOVA 352\u003c\/p\u003e \u003cp\u003e\u003cb\u003e15 Repeated Measures \u003c\/b\u003e\u003cb\u003e355\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e15.1 Repeated Measures ANOVA 355\u003c\/p\u003e \u003cp\u003e15.2 Repeated Measures ANOVA with Two Factors 359\u003c\/p\u003e \u003cp\u003e15.3 ANOVA with Several Repeated Measures 361\u003c\/p\u003e \u003cp\u003e15.4 Multivariate Tests 362\u003c\/p\u003e \u003cp\u003e\u003cb\u003e16 Clinical Trials \u003c\/b\u003e\u003cb\u003e363\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e16.1 Classification of Clinical Trials 363\u003c\/p\u003e \u003cp\u003e16.2 The Clinical Trial Population 365\u003c\/p\u003e \u003cp\u003e16.3 The Efficacy Criteria 366\u003c\/p\u003e \u003cp\u003e16.4 Controlled Clinical Trials 367\u003c\/p\u003e \u003cp\u003e16.5 The Control Group 369\u003c\/p\u003e \u003cp\u003e16.6 Blinding 370\u003c\/p\u003e \u003cp\u003e16.7 Randomization 371\u003c\/p\u003e \u003cp\u003e16.8 Non-comparative Clinical Trials 375\u003c\/p\u003e \u003cp\u003e16.9 Regression Toward the Mean 378\u003c\/p\u003e \u003cp\u003e16.10 Non-randomized Controlled Clinical Trials 379\u003c\/p\u003e \u003cp\u003e16.11 Classical Randomized Clinical Trial Designs 381\u003c\/p\u003e \u003cp\u003e16.12 Alternative Clinical Trial Designs 385\u003c\/p\u003e \u003cp\u003e16.13 Pragmatic Clinical Trials 387\u003c\/p\u003e \u003cp\u003e16.14 Cluster Randomized Trials 389\u003c\/p\u003e \u003cp\u003e16.15 The Size of a Clinical Trial 393\u003c\/p\u003e \u003cp\u003e16.16 Non-inferiority Clinical Trials 398\u003c\/p\u003e \u003cp\u003e16.17 Adaptive Clinical Trials 403\u003c\/p\u003e \u003cp\u003e16.18 Group Sequential Plans 405\u003c\/p\u003e \u003cp\u003e16.19 The Alpha Spending Function 407\u003c\/p\u003e \u003cp\u003e16.20 The Clinical Trial Protocol 409\u003c\/p\u003e \u003cp\u003e16.21 The Data Record 411\u003c\/p\u003e \u003cp\u003e\u003cb\u003e17 Analysis of Clinical Trials \u003c\/b\u003e\u003cb\u003e413\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e17.1 General Analysis Plan 413\u003c\/p\u003e \u003cp\u003e17.2 Data Preparation 414\u003c\/p\u003e \u003cp\u003e17.3 Study Populations 415\u003c\/p\u003e \u003cp\u003e17.4 Primary Efficacy Analysis 418\u003c\/p\u003e \u003cp\u003e17.5 Analysis of Multiple Endpoints 420\u003c\/p\u003e \u003cp\u003e17.6 Secondary Analyses 423\u003c\/p\u003e \u003cp\u003e17.7 Safety Analysis 424\u003c\/p\u003e \u003cp\u003e\u003cb\u003e18 Meta-analysis \u003c\/b\u003e\u003cb\u003e427\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e18.1 Purpose of Meta-analysis 427\u003c\/p\u003e \u003cp\u003e18.2 Measures of Effect 428\u003c\/p\u003e \u003cp\u003e18.3 The Inverse Variance Method 429\u003c\/p\u003e \u003cp\u003e18.4 The Random Effects Model 435\u003c\/p\u003e \u003cp\u003e18.5 Heterogeneity 439\u003c\/p\u003e \u003cp\u003e18.6 Publication Bias 442\u003c\/p\u003e \u003cp\u003e18.7 The Forest Plot 444\u003c\/p\u003e \u003cp\u003eReferences 447\u003c\/p\u003e \u003cp\u003eIndex 455\u003c\/p\u003e  \u003cp\u003e\u003cb\u003eA. GOUVEIA OLIVEIRA\u003c\/b\u003e is a M.D. with a PhD in Biostatistics from the University of Lisbon, Portugal. For the last 20 years, he has been dedicated to clinical and basic research. He was the founder and CEO of Datamedica, a full-service Contract Research Organization based in Lisbon, Portugal, where he designed, conducted and analyzed a large number of epidemiologic studies and clinical trials for all the major pharmaceutical companies. He was Associate Professor of Biomedical Informatics at the Medical University of South Carolina, USA, and currently Associate Professor of Biostatistics in the Pharmaceutical Sciences Department of the Federal University of Rio Grande do Norte in Natal, Brazil. He is the author or co-author of over 100 papers published in leading scientific journals.   \u003c\/p\u003e\u003cp\u003e\u003cb\u003eTHE ESSENTIAL REFERENCE FOR ANY CRITICAL APPRAISAL OF STATISTICAL METHODOLOGY\u003c\/b\u003e \u003c\/p\u003e\u003cp\u003e\u003ci\u003eBiostatistics Decoded\u003c\/i\u003e, \u003ci\u003e2nd Edition\u003c\/i\u003e provides a unique and well-rounded approach to the teaching of statistical methods. It offers a foundational and basic treatment of the mathematics grounding its subject matter, allowing health professionals and researchers alike to grasp its concepts with ease. The book serves readers with different levels of understanding of the subject, offering both an introductory and more advanced level of material within each chapter. The text is written and organized in a clear and concise way so that each level can be easily explored without loss of continuity. \u003c\/p\u003e\u003cp\u003eThis new edition of \u003ci\u003eBiostatistics Decoded\u003c\/i\u003e contains a wealth of new resources, including: \u003c\/p\u003e\u003cul\u003e \u003cli\u003eExtensive coverage of the design and analysis of experiments for basic science research\u003c\/li\u003e \u003cli\u003eExperimental designs presented together with the statistical methods\u003c\/li\u003e \u003cli\u003eThe rationale of all forms of ANOVA explained with simple mathematics\u003c\/li\u003e \u003cli\u003eA comprehensive presentation of statistical tests for multiple comparisons\u003c\/li\u003e \u003cli\u003eCalculations for all statistical methods, with examples and step-by-step instructions\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003e\u003ci\u003eBiostatistics Decoded\u003c\/i\u003e is perfect for anyone with an interest in the statistical methods underlying experimental research, regardless of their abilities in mathematics.\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47988842430693,"sku":"NP9781119584209","price":98.5,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9781119584209.jpg?v=1761781737","url":"https:\/\/k12savings.com\/products\/biostatistics-decoded-isbn-9781119584209","provider":"K12savings","version":"1.0","type":"link"}