Kindly note that we have put a lot of effort into researching the best books on Statistical Methods of Analysis and Design subject and came out with a recommended list of top 10 best books. The table below contains the Name of these best books, their authors, publishers and an unbiased review of books on "Statistical Methods of Analysis and Design" as well as links to the Amazon website to directly purchase these books. As an Amazon Associate, we earn from qualifying purchases, but this does not impact our reviews, comparisons, and listing of these top books; the table serves as a ready reckoner list of these best books.
|1. “Engineering Statistics” by A B Bowker and G J Liberman|
|2. “Statistics and Experimental Design in Engineering and the Physical Sciences” by N L Johnson and F C Xeen Leone|
|3. “Probability and Statistical Inference” by R V Hogg and E A Tanis
“Probability and Statistical Inference” Book Review: This applied introduction to the mathematics of probability and statistics concentrate on the existence of variation in almost every process, and how the study of probability and statistics helps us understand this variation. This book has a student-friendly approach along with a solid organisation of knowledge and has a balanced coverage of the topic. The book is divided into eleven topics they are Probability, Discrete Distributions, Continuous Distributions, Bivariate Distributions, Distributions of Functions of Random Variables, Estimation, Tests of Statistical Hypotheses, Nonparametric Methods, Bayesian Methods, Some Theory, Quality Improvement Through Statistical Methods along with some references and exercises.
| 4. “The Design and Statistical Analysis of Animal Experiments” by Dr Simon T Bate and Dr Robin A Clark
“The Design and Statistical Analysis of Animal Experiments” Book Review: his book is a comprehensive guide to the design and statistical analysis of animal experiments. This book explains the statistical tools employed by practitioners by making real life experiments. This book includes a range of design types they are block, factorial, nested, cross-over, dose-escalation and repeated measures so as to analyse the data generated experimentally. The book is simple and describes in non-mathematical terms, helping readers without a statistical background to understand key techniques. This book includes topics like Statistical concepts, Experimental design, Randomisation, Statistical analysis, Analysis using In VivoStat along with some references and index.
| 5. “Design of Experiments: Statistical Principles of Research Design and Analysis” by Robert
“Design of Experiments: Statistical Principles of Research Design and Analysis” Book Review: This book provides an overall view of the subject and provides a realistic setting as possible for conducting an actual research project. This book includes all design strategies and emphasizes hypotheses related to treatment design. This book has real world examples which are actually based on research studies. This book makes us know not why to apply but how to apply the theories along with identifying a treatment design that addresses the problem. This book has numerous examples which are based on actual studies & real data. This book is divided into 17 chapters they are. Research Design Principles, Getting Started with Completely Randomized Designs, Treatment Comparisons, Diagnosing Agreement Between the Data and the Model, Experiments to Study Variances, Factorial Treatment Designs, Factorial Treatment Designs: Random and Mixed Models, Complete Block Designs, Incomplete Block Designs: An Introduction, Resolvable and Cyclic Designs, Factorial Treatment Designs, Fractional Factorial Designs, Response Surface Designs, Split-Plot Designs, Repeated Measures Designs, Crossover Designs, Analysis of Covariance.
| 6. “Propensity Score Analysis: Statistical Methods and Applications” by Shenyang Guo and Mark W Fraser
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“Propensity Score Analysis: Statistical Methods and Applications” Book Review: This book covers the subject in a systematic manner with review of the origins, history, and statistical foundations and illustrates how to use methods for solving evaluation problems. This book focuses on practical applications of various types of data and evaluation problems, strategies for using the methods along with covering the limitations. This book covers topics like Counterfactual Framework and Assumptions, Conventional Methods for Data Balancing, Sample Selection and Related Models, Propensity Score Matching and Related Models, Propensity Score Subclassification, Propensity Score Weighting, Matching Estimators, Propensity Score Analysis With Nonparametric Regression, Propensity Score Analysis of Categorical or Continuous Treatments: Dosage Analyses, Selection Bias and Sensitivity Analysis, etc along with some remarks and Examples.
| 7. “An Introduction to Statistical Methods and Data Analysis” by R Lyman Ott and Micheal T Longnecker
“An Introduction to Statistical Methods and Data Analysis” Book Review: This book covers the topic very well and provides a broad overview of statistical methods for advanced undergraduate and graduate students from a variety of disciplines who have little or no prior coursework in statistics. This book helps the reader to be critical to the subject and to make decisions based on data and solving real world problems. This book covers topics such as Statistics, Using Surveys and Scientific Studies to Gather Data, Data Description, Probability and Probability Distributions, Inferences about Population Central Values, Inferences Comparing Two Population Central Values, Inferences about Population Variances, Inferences about More Than Two Population Central Values. It also covers some advanced topics like Multiple Comparisons, Categorical Data, Linear Regression and Correlation, Multiple Regression and the General Linear Model, More on Multiple Regression, Design Concepts for Experiments and Studies, Analysis of Variance for Standard Designs, Communicating and Documenting the Results of Analyses, etc in detail.
| 8. “Statistical Methods for Psychology” by David C Howell
“Statistical Methods for Psychology” Book Review: This book is resourceful and easy to understand and has the statistical techniques commonly used in the behavioral and social sciences, particularly psychology and education. This book emphasizes conceptual understanding so that students gain a better understanding of the specific statistical hypothesis tests that are covered throughout the text.This book focuses on two things first is the importance of looking at the data before beginning a hypothesis test, and the second is the importance of knowing the relationship between the statistical test in use. This book is divided into sub topics and they are Describing and Exploring Data, The Normal Distribution, Sampling Distributions and Hypothesis Testing, Basic Concepts of Probability, Categorical Data and Chi-Square, Hypothesis Tests Applied to Means, Power, Correlation and Regression, Alternative Correlational Techniques, Simple Analysis of Variance, Multiple Comparisons Among Treatment Means, Multiple Comparisons Among Treatment Means, Repeated-Measures Designs, Multiple Regression, Analyses Of Variance and Covariance as General Linear Models, Meta-Analysis and Single-Case Designs, etc.
| 9. “Factor Analysis: Statistical Methods and Practical Issues” by Jae-On Kim and Charles W Mueller
“Factor Analysis: Statistical Methods and Practical Issues” Book Review: This book covers the topic well and focuses on exploratory factor analysis, confirmatory factor analysis and various methods of constructing factor scales. This book covers the topics like The conceptual foundation of factor analysis, Methods of Extracting Initial Factors, Methods of Rotation, Number of Factors Problem Revisited, Introduction to Confirmatory Factor Analysis, Construction of Factor Scales are also explained with examples. The book describes initial factoring and factor rotation in detail.
| 10. “The Statistical Analysis of Experimental Data” by John Mandel
“The Statistical Analysis of Experimental Data” Book Review: This book offers precise measurements with numerous problems. The book here draws a clear and fascinating blueprint for a systematic science of statistical analysis. This book approaches with examples aimed specifically at statistical problems. This book comprises a thorough grounding in the fundamental mathematical definitions, concepts, and facts underlying modern statistical theory. The book determines the most effective methodology using statistics as an interpretative tool. This book also includes many examples which are worked step by step and helpful figures and tables with summary of the chapters, the chapters are The Nature of Measurement, Statistical Models and Statistical Analysis, The Mathematical Framework of Statistics Part, The Mathematical Framework of Statistics Part, Homogeneous Sets of Measurements, The Precision and Accuracy of Measurements, The Method of Least Squares, Testing the Statistical Model, The Analysis of Structured Data, Some Principles of Sampling, The Fitting of Curves and Surfaces, The Fitting of Straight Lines, etc.
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