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Biostatistics DeMYSTiFied

Biostatistics DeMYSTiFied

9780071600415
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Description

A self-teaching guide to all the statistical procedures used in all medical disciplines

Offering broad coverage of all the statistical procedures used in all medical disciplines, this book is the ideal course companion and self-study tool. This easy-to-use guide clearly shows how to use counts and measurements to carry out description, comparison, correlation, and prediction in the biomedical field, and how to evaluate data accordingly. The book uses practical medical examples to improve students grasp of biostatistical analyses and features end-of-chapter quizzes and a final exam to test knowledge.

Product Details
McGraw Hill / Medical
49156
9780071600415
9780071600415

Data sheet

Publication date
2014
Issue number
1
Cover
paperback
Pages count
320
  • Chapter 1. Introduction:: Variability of biological attributes and random action of determinants; Definition of statistics and biostatistics; Using tables of random numbers in random sampling; Averages and means; Variance and standard deviation; Essential definitions; Data of organization, tables, diagrams, and graphs; Historical note; Chapter 2. Numbers and significant figuresCardinal and ordinal numbers; Continuous vs. discrete numbers; Rules for significant figures; Units, dimensions, and equations; Rates and ratios; Transpositions and conversions; Using table of random numbers for random sampling; Chapter 3. Proportions and probabilityProbability defined; Structural, empirical, and subjective probabilities; Addition and multiplication rules; The sample space rectangle; Bernoullian binary probability; Sets, elements, and trials; Binomial expansion; Poisson distribution; Beginning of probability theory Fermat and Pascal; Chapter 4. Gaussian normal frequency distributionCharacteristics of the normal frequency distribution curve of biological attributes; The central limit theorem; Sorting; Confidence limits; Students t test for small samples; Chapter 5. Differences and deviations; The chi square distribution; Analysis of variance; Chapter 6. The management of large samples; The law of large numbers; Labor saving procedure; Charliers check; Chapter 7. Comparing two means in 2x2 contingency tables; Difference in a pair of measured means; Difference in a pair of counts; Comparison of counts expressing conditional probabilities; Yates correction; Small samples (the Exact Method); Chapter 8. Conditional probability; Mutually exclusive vs. independent attributes; Sample space rectangle for conditional probabilities; Boolean notation for conditional probabilities; Bayes theorem; Chapter 9. Correlation and linear regressionCartesian coordinates; Correlation vs. coincidence; Dependent and independent variables; Standard error of estimate
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