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Intuitive Biostatistics : A Nonmathematica
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eBay item number:204768737851
Item specifics
- Condition
- Like New
- Seller notes
- Subject
- Statistics
- ISBN
- 9780190643560
- Publication Year
- 2017
- Type
- Textbook
- Format
- Trade Paperback
- Language
- English
- Publication Name
- Intuitive Biostatistics : a Nonmathematical Guide to Statistical Thinking
- Item Height
- 1.2in
- Item Length
- 6.1in
- Publisher
- Oxford University Press, Incorporated
- Item Width
- 9.1in
- Item Weight
- 28.2 Oz
- Number of Pages
- 608 Pages
About this product
Product Information
Intuitive Biostatistics takes a non-technical, non-quantitative approach to statistics and emphasizes interpretation of statistical results rather than the computational strategies for generating statistical data. This makes the text especially useful for those in health-science fields who have not taken a biostatistics course before. The text is also an excellent resource for professionals in labs, acting as a conceptually oriented and accessiblebiostatistics guide. With an engaging and conversational tone, Intuitive Biostatistics provides a clear introduction to statistics for undergraduate and graduate students and also serves as a statistics refresher forworking scientists.
Product Identifiers
Publisher
Oxford University Press, Incorporated
ISBN-10
0190643560
ISBN-13
9780190643560
eBay Product ID (ePID)
239735365
Product Key Features
Publication Name
Intuitive Biostatistics : a Nonmathematical Guide to Statistical Thinking
Format
Trade Paperback
Language
English
Publication Year
2017
Type
Textbook
Number of Pages
608 Pages
Dimensions
Item Length
6.1in
Item Height
1.2in
Item Width
9.1in
Item Weight
28.2 Oz
Additional Product Features
Lc Classification Number
R853.S7m68 2018
Edition Number
4
Reviews
"This splendid book meets a major need in public health, medicine, and biomedical research training. It is a user-friendly biostatistics text for non-mathematicians that clearly explains how to make sense of statistical results, avoid common mistakes in data analysis, avoid being confused bystatistical nonsense, and how to make research more reproducible. Students may enjoy statistics for the first time!" --Gilbert S. Omenn, University of Michigan, "This splendid book meets a major need in public health, medicine, and biomedical research training. It is a user-friendly biostatistics text for non-mathematicians that clearly explains how to make sense of statistical results, avoid common mistakes in data analysis, avoid being confused by statistical nonsense, and how to make research more reproducible. Students may enjoy statistics for the first time!"--Gilbert S. Omenn, University of Michigan"This book applies what I would call "scientific common sense" to the confusing world of statistical analysis and interpretation. If you want to really understand what a p-value is, read this book." -- Louis G. Zachos, University of Mississippi"Intuitive Biostatistics places statistical concepts and practical issues of data analysis within an understandable light. The textbook helps the reader grasp the fundamentals and the pitfalls of data presentation and analysis. It should be on the "must-read" list of clinicians, journal reviewers, editors, and other consumers of scientific literature." -- John D. Bonagura, The Ohio State University"I have already recommend the book to many colleagues. A concise, well written, and at times funny book that clearly explains the most important conceptual aspects about statistics, emphasizing proper interpretation of results and common mistakes to avoid." -- Walter E. Schargel, The University of Texas at Arlington
Table of Content
Part A. Introducing Statistics 1. Statistics and Probability are not Intuitive 2. The Complexities of Probability 3. From Sample to Population Part B. Introducing Confidence Intervals 4. Confidence Interval of a Proportion 5. Confidence Interval of Survival Data 6. Confidence Interval of Counted Data (Poisson Distribution) Part C. Continuous Variables 7. Graphing Continuous Data 8. Types of Variables 9. Quantifying Scatter 10. The Gaussian Distribution 11. The Lognormal Distribution and Geometric Mean 12. Confidence Interval of a Mean 13. The Theory of Confidence Intervals 14. Error Bars Part D. P Values and Statistical Significance 15. Introducing P Values 16. Statistical Significance and Hypothesis Testing 17. Comparing Groups with Confidence Intervals and P Values 18. Interpreting a Result That Is Statistically Significant 19. Interpreting a Result That Is Not Statistically Significant 20. Statistical Power 21. Testing For Equivalence or Noninferiority Part E. Challenges in Statistics 22. Multiple Comparisons Concepts 23. The Ubiquity of Multiple Comparisons 24. Normality Tests 25. Outliers 26. Choosing a Sample Size Part F. Statistical Tests 27. Comparing Proportions 28. Case-Control Studies 29. Comparing Survival Curves 30. Comparing Two Means: Unpaired t Test 31. Comparing Two Paired Groups 32. Correlation Part G. Fitting Models to Data 33. Simple Linear Regression 34. Introducing Models 35. Comparing Models 36. Nonlinear Regression 37. Multiple Regression 38. Logistic and Proportional Hazards Regression Part H. The Rest of Statistics 39. Analysis of Variance 40. Multiple Comparison Tests after ANOVA 41. Nonparametric Methods 42. Sensitivity, Specificity, and Receiver-Operating Characteristic Curves 43. Meta-Analysis Part I. Putting It All Together 44. The Key Concepts of Statistics 45. Statistical Traps to Avoid 46. Capstone Example 47. Statistics and Reproducibility 48. Checklists for Reporting Statistical Methods and Results Part J. Appendices, Part A. Introducing Statistics1. Statistics and Probability are not Intuitive2. The Complexities of Probability3. From Sample to PopulationPart B. Introducing Confidence Intervals4. Confidence Interval of a Proportion5. Confidence Interval of Survival Data6. Confidence Interval of Counted Data (Poisson Distribution)Part C. Continuous Variables7. Graphing Continuous Data8. Types of Variables9. Quantifying Scatter10. The Gaussian Distribution11. The Lognormal Distribution and Geometric Mean12. Confidence Interval of a Mean13. The Theory of Confidence Intervals14. Error BarsPart D. P Values and Statistical Significance15. Introducing P Values16. Statistical Significance and Hypothesis Testing17. Comparing Groups with Confidence Intervals and P Values18. Interpreting a Result That Is Statistically Significant19. Interpreting a Result That Is Not Statistically Significant20. Statistical Power21. Testing For Equivalence or NoninferiorityPart E. Challenges in Statistics22. Multiple Comparisons Concepts23. The Ubiquity of Multiple Comparisons24. Normality Tests25. Outliers26. Choosing a Sample SizePart F. Statistical Tests27. Comparing Proportions28. Case-Control Studies29. Comparing Survival Curves30. Comparing Two Means: Unpaired t Test31. Comparing Two Paired Groups32. CorrelationPart G. Fitting Models to Data33. Simple Linear Regression34. Introducing Models35. Comparing Models36. Nonlinear Regression37. Multiple Regression38. Logistic and Proportional Hazards RegressionPart H. The Rest of Statistics39. Analysis of Variance40. Multiple Comparison Tests after ANOVA41. Nonparametric Methods42. Sensitivity, Specificity, and Receiver-Operating Characteristic Curves43. Meta-AnalysisPart I. Putting It All Together44. The Key Concepts of Statistics45. Statistical Traps to Avoid46. Capstone Example47. Statistics and Reproducibility48. Checklists for Reporting Statistical Methods and ResultsPart J. Appendices
Copyright Date
2018
Topic
Biostatistics, Life Sciences / General, Research, Life Sciences / Biology
Lccn
2017-048570
Dewey Decimal
610.72/1
Intended Audience
College Audience
Dewey Edition
22
Illustrated
Yes
Genre
Science, Medical
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eBay item number:204768737851
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