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## Details

Document Type: | Book |
---|---|

All Authors / Contributors: |
James E De Muth |

ISBN: | 9781466596733 1466596732 |

OCLC Number: | 862102612 |

Description: | xxvi, 821 pages : illustrations ; 25 cm. |

Contents: | 1. Introduction -- Types of Statistics -- Parameters and Statistics -- Sampling and Independent Observations -- Types of Variables -- Independent and Dependent Variables -- Selection of the Appropriate Statistical Test -- Procedures for Inferential Statistical Tests -- Applications of Computer Software -- References -- Suggested Supplemental Readings -- Example Problems -- 2. Probability -- Classic Probability -- Probability Involving Two Variables -- Conditional Probability -- Probability Distribution -- Counting Techniques -- Binomial Distribution -- Poisson Distribution -- References -- Suggested Supplemental Readings -- Example Problems -- 3. Sampling -- Random Sampling -- Using Minitab® or Excel® to Generate a Random Sample -- Other Probability Sampling Procedures -- Nonprobability Sampling Procedure -- Random Assignment to Two or More Experimental Levels -- Precision, Accuracy, and Bias -- Reliability and Validity. Suggested Supplemental Readings -- Example Problems -- 4. Presentation Modes -- Tabulation of Data -- Visual Displays for Discrete Variables -- Visual Displays for Continuous Variables -- Visual Displays for Two or More Continuous Variables -- Using Excel® or Minitab® for Visual Displays -- References -- Suggested Supplemental Readings -- Example Problems -- 5. Measures of Central Tendency -- Centers of a Continuous Distribution -- Dispersion within a Continuous. Distribution -- Population versus Sample Measures of Central Tendency -- Measurements Related to the Sample Standard Deviation -- Trimmed Mean -- Using Excel® or Minitab® for Measures of Central Tendency -- Alternative Computational Methods for Calculating Central Tendency -- References -- Suggested Supplemental Readings -- Example Problems -- 6. The Normal Distribution and Data Transformation -- The Normal Distribution -- Determining if the Distribution is Normal. Data Transformations: An Overview -- Lognormal Transformation and the Geometric Mean -- Other Types of Transformations -- Using Excel® or Minitab® to Evaluate Normality -- References -- Suggested Supplemental Readings -- Example Problems -- 7. Confidence Intervals and Tolerance Limits -- Sampling Distribution -- Standard Error of the Mean versus the Standard Deviation -- Confidence Intervals -- Statistical Control Charts -- Process Capability Indices -- Tolerance Limits -- Using Excel® or Minitab® for Applications Discussed in this Chapter -- References -- Suggested Supplemental Readings -- Example Problems -- 8. Hypothesis Testing -- Hypothesis Testing -- Types of Errors -- Type I Error -- Type II Error and Power -- Experimental Errors and Propagation of Errors -- References -- Suggested Supplemental Readings -- Example Problems -- 9.t-Tests -- Parametric Procedures -- The t-Distribution -- One-Tailed versus Two-Tailed Tests -- One-Sample t-Tests. Two-Sample t-Tests -- Computer Generated p-values -- Corrected Degrees of Freedom for Unequal Variances -- One-Sample t-Test Revisited for Critical Value -- Matched Pair t-Test (Difference t-Test) -- Using Excel® or Minitab® for Student t-tests -- References -- Suggested Supplemental Readings -- Example Problems -- 10. One-Way Analysis of Variance (ANOVA) -- Hypothesis Testing with the One-Way ANOVA -- The F-Distribution -- Test Statistic -- ANOVA Definitional Formula -- ANOVA Computational Formula -- Randomized Block Design -- Homogeneity of Variance -- Using Excel® or Minitab® for One-Way ANOVAs -- References -- Suggested Supplemental Readings -- Example Problems -- 11. Multiple Comparison Tests -- Error Associated with Multiple t-Tests -- Overview of Multiple Comparison Tests -- The q-Statistic -- Planned Multiple Comparisons -- Bonferroni Adjustment -- Sidak Test -- Dunn's Multiple Comparisons -- Dunnett's Test -- Post Hoc Procedures. Tukey HSD Test -- Student Newman-Keuls Test -- Fisher LSD Test -- Scheffe Procedure -- Scheffe Procedure for Complex Comparisons -- Unbalanced Designs -- Lack of Homogeneity -- Other Post Hoc Tests -- Using Minitab® for Multiple Comparisons -- References -- Suggested Supplemental Readings -- Example Problems -- 12. Factorial Designs: An Introduction -- Factorial Designs -- Two-Way Analysis of Variance -- Computational Formula with Unequal Cell Size -- Post Hoc Procedures -- Repeated Measures Design -- Repeatability and Reproducibility -- Latin Square Designs -- Other Designs -- Fixed, Random and Mixed Effect Models -- Beyond a Two-Way Factorial Design -- Using Excel® or Minitab® for Two-Way ANOVAs -- References -- Suggested Supplemental Readings -- Example Problems -- 13. Correlation -- Graphic Representation of Two Continuous Variables -- Covariance -- Pearson Product-Moment Correlation Coefficient -- Correlation Line. Statistical Significance of a Correlation Coefficient -- Correlation and Causality -- In Vivo and In Vitro Correlation -- Other Types of Bivariate Correlations -- Pair-wise Correlations Involving More Than Two Variables -- Multiple Correlations -- Partial Correlations -- Nonlinear Correlations -- Assessing Independence and Randomness -- Using Excel® or Minitab® for Correlation -- References -- Suggested Supplemental Readings -- Example Problems -- 14. Regression Analysis -- The Regression Line -- Coefficient of Determination -- ANOVA Table -- Confidence Intervals and Hypothesis Testing for the Population -- Slope ([beta]) -- Confidence Intervals and Hypothesis Testing for the Population Intercept ([alpha]) -- Confidence Intervals for the Regression Line -- Inverse Prediction -- Multiple Data at Various Points on the Independent Variable -- Lack-of-fit Test -- Assessing Parallelism of the Slopes of Two Samples -- Curvilinear and Non-linear Regression. Multiple Linear Regression Models -- Stepwise Regression -- Using Excel® or Minitab® for Regression -- References -- Suggested Supplemental Readings -- Example Problems -- 15.z-Tests of Proportions -- z-Test of Proportions -- One-Sample Case -- z-Test of Proportions -- Two-Sample Case -- Power and Sample Size for Two-Sample z-Test of Proportions -- z-Tests for Proportions -- Yates' Correction for Continuity -- Proportion Testing for More Than Two Levels of a Discrete Independent Variable -- Using Minitab® for z-Tests of Proportion -- References -- Suggested Supplemental Readings -- Example Problems -- 16. Chi Square Tests -- Chi Square Statistic -- Chi Square for Goodness-of-Fit for One Discrete Dependent Variable -- Chi Square for One Discrete Dependent Variable and Equal Expectations -- Chi Square Goodness-of-Fit Test for Distributions -- Chi Square Test of Independence -- Chi Square Test for Trend for Ordinal Classifications. Yates' Correction for Two-by-Two Contingency Table -- Likelihood-Ratio Chi Square Test -- Comparison of Chi Square to the z-Test of Proportions -- Fisher's Exact Test -- McNemar's Test -- Cochran's Q Test -- Mantel-Haenszel Test -- Using Excel® or Minitab® for Chi Square Applications -- References -- Suggested Supplemental Readings -- Example Problems -- 17. Measures of Association -- Introduction -- Dichotomous Associations -- Nominal Associations -- Ordinal Associations -- Nominal-by-Interval Associations -- Reliability Measurements -- Summary -- References -- Suggested Supplemental Readings -- Example Problems -- 18. Odds Ratios and Relative Risk Ratios -- Probability, Odds, and Risk -- Odds Ratio -- Relative Risk -- Graphic Display for Odds Ratios and Relative Risk Ratios -- Mantel-Haenszel Estimate of Relative Risk -- Logistic Regression -- References -- Suggested Supplemental Readings -- Example Problems. 19. Evidence-Based Practice: An Introduction -- Sensitivity and Specificity -- Two-by-Two Contingency Table -- Defining Evidence-Based Practice -- Frequentist versus Bayesian Approaches to Probability -- Predictive Values -- Likelihood Ratios -- References -- Suggested Supplemental Readings -- Example Problems -- 20. Survival Statistics -- Censored Survival Data -- Life Table Analysis -- Survival Curve -- Kaplan-Meier Procedure -- Visual Comparison of Two Survival Curves -- Tests to Compare Two Levels of an Independent Variable -- Hazard Ratios -- Multiple Regression with Survival Data: Proportional Hazards Regression -- Wilcoxon Test -- Other Measures and Tests of Survival -- Survival Statistics Using Minitab® -- References -- Suggested Supplemental Readings -- Example Problems -- 21. Nonparametric Tests -- Use of Nonparametric Tests -- Ranking of Information -- Estimating the Median Based on Walsh Averages -- One-Sample Sign Test. Wilcoxon Signed-Ranks Test -- Mann-Whitney Test -- Two-Sample Median Test -- Wilcoxon Matched-Pairs Test -- Sign Test for Paired Data -- Kruskal-Wallis Test -- Post Hoc Comparisons Using Kruskal-Wallis -- Mood's Median Test -- Friedman Two-Way Analysis of Variance -- Spearman Rank-Order Correlation -- Kendall's Coefficient of Concordance -- Theil's Incomplete Method -- Kolmogorov-Smirnov Goodness-of-Fit Test -- Anderson-Darling Test -- Runs Tests -- Range Tests -- Nonparametric Tests Using Minitab® -- References -- Suggested Supplemental Readings -- Example Problems -- 22. Statistical Tests for Equivalence -- Bioequivalence Testing -- Experimental Designs for Bioequivalence Studies -- Two-Sample t-Test Example -- Power izn Bioequivalence Tests -- Rules for Bioequivalence -- Creating Confidence Intervals -- Comparison Using Two One-Sided t-Tests -- Clinical Equivalence -- Superiority Studies -- Noninferiority Studies -- Dissolution Testing. SUPAC-IR Guidance -- Equivalent Precision -- References -- Suggested Supplemental Readings -- Example Problems -- 23. Outlier Tests -- Regulatory Considerations -- Outliers on a Single Continuum -- Plotting and the Number of Standard Deviations from the Center -- The "Huge" Rule -- Grubbs' Test for Outlying Observations -- Dixon Q Test -- Hampel's Rule -- Multiple Outliers -- Bivariate Outliers in Correlation and Regression Analysis -- References -- Suggested Supplemental Readings -- Example Problems -- 24. Statistical Errors in the Literature -- Errors and the Peer Review Process -- Problems with Experimental Design -- Standard Deviations versus Standard Error of the Mean -- Problems with Hypothesis Testing -- Problems with Parametric Statistics -- Errors with the Chi Square Test of Independence -- Summary -- References -- Suggested Supplemental Readings -- Appendix A Flow Charts for the Selection of Appropriate Tests -- Appendix B Statistical Tables. B1. Random "Numbers Table -- B2. Normal Standardized Distribution -- B3.K-Values for Calculating Tolerance Limits (Two-Tailed) -- B4.K-Values for Calculating Tolerance Limits (One-Tailed) -- B5. Student t-Distribution (1 -- [alpha]/2) -- B6.Comparison of One-tailed versus Two-Tailed t-Distributions -- B7. Analysis of Variance F-Distribution -- B8. Upper Percentage Points of the Fmax Statistic -- B9. Upper Percentage Points of the Cochran C Test for Homogeneity of Variance -- B10. Percentage Points of the Standardized Range (q) -- B11. Percentage Points of the Dunn Multiple Comparisons -- B12. Critical Values of q for the Two-Tailed Dunnett's Test -- B13. Critical Values of q for the One-Tailed Dunnett's Test -- B14. Values of r at Different Levels of Significance -- B15. Chi Square Distribution -- B16. Binomial Distributions where p = 0.50 -- B17. Critical Values of the Wilcoxon T Distribution. B18. Critical Values for Kolmogorov Goodness-of-Fit Test ([alpha] = 0.05) -- B19. Critical Values for Smirnov Test Statistic ([alpha] = 0.05) -- B20. Critical Values for the Runs Test ([alpha] = 0.05) -- B21. Critical Values for TI Range Test ([alpha] = 0.05) -- B22. Critical Values for the FR Test for Dispersion -- B23. Values for Use in Grubbs' Test for Outlier ([alpha]) -- B24. Values for Use in Dixon Test for Outlier ([alpha]) -- Appendix C Summary of Commands for Excel® and Minitab® -- Appendix D Answers to Example Problems. |

Series Title: | CRC Press pharmacy education series. |

Responsibility: | James E. De Muth, Professor, School of Pharmacy, University of Wisconsin-Madison. |

### Abstract:

"Preface The first two editions of this book were published thirteen and eight years ago. The first edition was a fairly successful attempt to provide a practical, easy-to-read, basic statistics book for two primary audiences, those in the pharmaceutical industry and those in pharmacy practice. Reviewing the contents and current uses of the first edition, several shortcomings were identified, corrected and greatly expanded in the second edition. This third edition represents not only an update of the previous two editions, but a continuing expansion on topics relevant to both intended audiences. As described later, most of the expanded information in this third edition related to allowing statistical software to accomplish the same results as identified through hand calculations. The author has been fortunate to have taught over 100 statistics short courses since the 1999 release of the first edition. Valuable input through the learners attending these classes and new examples from these individuals have been helpful in identifying missing materials in the previous editions. In addition, the author had the opportunity to work closely with a variety of excellent statisticians. Both of these activities have helped contribute to the updating and expansions since the first book. The continuing title of the book, Basic Statistics and Pharmaceutical Statistical Applications, is probably a misnomer. The goal of the first edition was to create an elementary traditional statistical textbook to explain tests commonly seen in the literature or required to evaluate simple data sets. By expanding the contents, primarily in the second edition, the material in this edition well exceeded what would be expected in a basic statistics book. A Book for Non-Statisticians"--

## Reviews

*Editorial reviews*

Publisher Synopsis

"The book's coverage ... is immense and very impressive. The book also well describes introductory statistics, and coverage of normal outcomes was exemplary. The multiple comparisons and nonparametric statistics chapters in particular were outstanding. The third edition has made notable improvements over the second edition in several chapters; there are too many to describe here. ... very well written and easy to read. ... very useful and unique reading, given its wide practical coverage and the approaches taken. I have added this book to my go-to reference sources ... a very good teaching introduction to statistics for undergraduate and graduate students ... This book may be most useful for persons involved in preclinical and Phase 1 studies where standard normal, binomial, and nonparametric methods are used."-Journal of Biopharmaceutical Statistics, 2015Praise for the Second Edition:"Dr. De Muth writes clearly about a very complex subject ... The second edition has been expanded and is an even more comprehensive description of the statistics used within the pharmaceutical industry and the health care system. ... a very useful reference tool for the pharmaceutical scientist and clinician..."-Frank J. Ascione, University of Michigan College of Pharmacy"De Muth has written a book that is both elegant and simple ... [it] enables the reader to clearly understand how to appropriately use statistics in designing studies and just as importantly determine when statistics should not be used ... an excellent reference book that will enable the non-statistician to appropriately use statistical approaches ... A unique attribute of this statistical textbook is the acknowledgement of how statistical tests can be misused ... useful information helps the non-statistician avoid some of the common errors that are made when using statistical approaches in the analysis of data."-Mark N. Milton, Millennium Pharmaceuticals, Inc."The book is laid out well, and the organization follows an intuitive path, beginning with an introduction to statistics that is appropriate for entry-level students. I found the appendix that focuses on statistical errors commonly encountered in the literature particularly enlightening. In summary, this book is an excellent choice for beginning or intermediate researchers interested in designing, implementing, and reporting statistically sound studies."-Dawn Boothe, DVM, PhD, DACVIM, DACVCP, Auburn University, Auburn, Alabama, Journal of the American Veterinary Medical Association, March 2015 Read more...

*User-contributed reviews*