Introduction to statistical data analysis for the life sciences. (2014)

• Record Type: Book
• Further Information: Note: Claus Thorn Ekstrøm, Helle Sørensen.
• Authors: Ekstrøm, Claus Thorn, 1971-; Sørensen, Helle, 1971-
• Contents: Description of Samples and Populations; Data types; Visualizing categorical data; Visualizing quantitative data; Statistical summaries; What is a probability?; R Linear Regression; Fitting a regression line; When is linear regression appropriate?; The correlation coefficient; Perspective; R Comparison of Groups; Graphical and simple numerical comparison; Between-group variation and within-group variation; Populations, samples, and expected values; Least squares estimation and residuals; Paired and unpaired samples; Perspective; R The Normal Distribution; Properties; One sample; Are the data (approximately) normally distributed?; The central limit theorem; R Statistical Models, Estimation, and Confidence Intervals; Statistical models; Estimation; Confidence intervals; Unpaired samples with different standard deviations; R Hypothesis Tests; Null hypotheses; t-tests; Tests in a one-way ANOVA; Hypothesis tests as comparison of nested models; Type I and type II errors; R Model Validation and Prediction; Model validation; Prediction; R Linear Normal Models; Multiple linear regression; Additive two-way analysis of variance; Linear models; Interactions between variables; R Non-Linear Regression; Non-linear regression models; Estimation, confidence intervals, and hypothesis tests; Model validation; R Probabilities; Outcomes, events, and probabilities; Conditional probabilities; Independence The Binomial Distribution; The independent trials model; The binomial distribution; Estimation, confidence intervals, and hypothesis tests; Differences between proportions; R Analysis of Count Data; The chi-square test for goodness-of-fit; 2 x 2 contingency table; Two-sided contingency tables; R Logistic Regression; Odds and odds ratios; Logistic regression models; Estimation and confidence intervals; Hypothesis tests; Model validation and prediction; R Statistical Analysis Examples; Water temperature and frequency of electric signals from electric eels; Association between listeria growth and RIP2 protein; Degradation of dioxin; Effect of an inhibitor on the chemical reaction rate; Birthday bulge on the Danish soccer team; Animal welfare; Monitoring herbicide efficacy Case Exercises; Case 1: Linear modeling; Case 2: Data transformations; Case 3: Two sample comparisons; Case 4: Linear regression with and without intercept; Case 5: Analysis of variance and test for linear trend; Case 6: Regression modeling and transformations; Case 7: Linear models; Case 8: Binary variables; Case 9: Agreement; Case 10: Logistic regression; Case 11: Non-linear regression; Case 12: Power and sample size calculations Appendix A: Summary of Inference Methods ; Appendix B: Introduction to R; Appendix C: Statistical Tables ; Appendix D: List of Examples Used throughout the Book Bibliography Index Exercises appear at the end of each chapter.
• Edition: Second edition
• Publisher Details: Boca Raton : Chapman & Hall/CRC
• Publication Date: 2014
• Extent: 1 online resource, illustrations
• Subjects: 570.15195; Life sciences -- Statistical methods; Mathematical statistics
• Languages: English
• ISBNs: 9781482238969; 9781482238945; 9781482238952
• Related ISBNs: 9781482238938
• Notes: Note: Includes bibliographical references and index.; Note: Description based on CIP data; item not viewed.
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
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