Statistics for Biology Students
Duxbury Press (Verlag)
978-0-534-38364-0 (ISBN)
- Titel wird leider nicht erscheinen
- Artikel merken
This handbook is selective in its coverage in order to emphasize hands-on, practical skills and knowledge. The author provides theoretical background only when needed to encourage an intelligent use of statistics and experimental design. Thus, the book is neither theory-driven nor superficial. With this short, succinct text, students can quickly read a chapter before doing the lab and grasp the necessary statistical principles before starting their data analysis. The presentation is driven by four basic questions students need to ask in research: 1.) I want to answer these particular questions in my research; what kind of experimental design is best? 2.) I've collected data; what is the best way to analyze them and what are the pitfalls? 3.) How should I interpret the results of the analysis? 4.) How should I report the results of the statistical analysis in a research paper?
Robert Arnold is a professor of biology at Colgate University, where he has taught since earning his Ph.D. at Simon Fraser University in British Columbia. His teaching specialties include biostatistics, plant physiology and ecology, and population biology. He has published numerous articles and papers in professional journals, notably in Canadian Journal of Botany, American Biology Teacher, Natural History, American Midland Naturalist, and The Journal of Plant Physiology.
1. WHEN DO BIOLOGISTS NEED STATISTICS? Frequency Data. Measurement Data. When Biologists Need Statistics. 2. DATA IN BIOLOGY. Variables and Variates. Samples and Populations. Measurement Scales for Variables. 3. DESCRIPTIVE STATISTICS. Measures of Central Tendency. Measures of Dispersion. Graphical Display of Descriptive Statistics. Reliability of a Sample Mean: The Standard Error. 4. COMPARING A SAMPLE WITH A STANDARD VALUE: ONE-SAMPLE t-TEST. The Standard Error and Confidence Intervals. Statistical Hypothesis Testing. Significance Levels for a Statistical Test. The t-Distribution. Type I and Type II Errors. One- and Two-Sided Tests. 5. COMPARING TWO OR MORE GROUPS: ANALYSIS OF VARIANCE. One-Way Analysis of Variance. Two-Way Analysis of Variance. More Complex Analysis of Variance Designs. 6. MEASURING ASSOCIATION BETWEEN VARIABLES: CORRELATION ANALYSIS. The Correlation Coefficient. Assumptions of Correlation Analysis Using Pearson?s R. Non-Parametric Analysis of Correlation. 7. FUNCTIONAL RELATIONSHIPS BETWEEN VARIABLES: REGRESSION ANALYSIS. Example. Is the Regression Significant? Uses of Regression Analysis. Multiple Regression Analysis. Non-Linear Regression Analysis. Analysis of Covariance. 8. ANALYSIS OF FREQUENCY DATA. An Example from Genetics. Statistical Test ? The G-Test. An Older Approach to Analysis of Frequencies ? The ?Chi-Square? Test. Contingency Tables. Comparisons among Proportions. GLOSSARY. INDEX.
| Erscheint lt. Verlag | 1.1.2019 |
|---|---|
| Sprache | englisch |
| Maße | 189 x 246 mm |
| Themenwelt | Mathematik / Informatik ► Mathematik ► Angewandte Mathematik |
| Mathematik / Informatik ► Mathematik ► Statistik | |
| Naturwissenschaften ► Biologie | |
| ISBN-10 | 0-534-38364-5 / 0534383645 |
| ISBN-13 | 978-0-534-38364-0 / 9780534383640 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
| Haben Sie eine Frage zum Produkt? |
aus dem Bereich
