Applied Statistics in Biology (eBook)

A Practical Guide Using SAS, R, and JMP

Stephen R. Bowley, Edzard Van Santen, Simon Riley, Diane K. Michelson, Ruth M. Hummel (Autoren)

eBook Download: PDF

2025 | 2. Auflage
882 Seiten
Acsess (Verlag)
9780891183969 (ISBN)

Infos

Understand applied statistics and its application in biology research Biology and its related sciences generate prodigious quantities of data through experimentation and observation. Interpreting this data and using it to generate statistically defensible inferences has become one of the most significant components of modern biological research. There are, however, very few up-to-date resources by which graduate students and researchers in biology can familiarize themselves with the key methodologies of applied statistics as they specifically connect to the applied life sciences. Applied Statistics in Biology remedies this oversight with a thorough, accessible overview to statistics and its biological applications. Beginning with the history and fundamentals of statistics, it covers all major statistical modes of analysis that biologists might find useful, with an eye towards a robust quantitative education for biologists. Fully up to date and addressing all conventional approaches to statistical analysis, it s a must-own for biology students and researchers alike. Applied Statistics in Biology readers will also find: Treatment rooted in years of graduate teaching in statistics and biologyDetailed discussion of topics including regression, non-Gaussian data, multivariate techniques, and many moreA valuable complement to existing resources on applied statistics Applied Statistics in Biology is ideal for graduate students in agriculture, biology, natural resources, and related fields, as well as for instructors and researchers in these and related subjects.

Produkt-Details

• Erscheint lt. Verlag: 26.8.2025
• Reihe/Serie: ASA, CSSA, and SSSA Books
• Sprache: englisch
• Themenwelt: Weitere Fachgebiete ► Land- / Forstwirtschaft / Fischerei
• Schlagworte: analysis of residuals • Distribution • Error Control • Factorial experiments • linear regression • non-Gaussian variance analysis • orthogonal polynomials • Rank correlation • Regression • regression in ANOVA • Statistical Analysis • transformations
• ISBN-13: 9780891183969 / 9780891183969