Buch, Englisch, 264 Seiten, Format (B × H): 234 mm x 164 mm, Gewicht: 410 g
Buch, Englisch, 264 Seiten, Format (B × H): 234 mm x 164 mm, Gewicht: 410 g
ISBN: 978-1-4665-8585-0
Verlag: Taylor & Francis Inc
The book begins with an overview of statistical software and the Stata program. It explains the various windows and menus and describes how they are integrated. The next chapters explore data entry and importing as well as basic output formats and descriptive statistics. The author describes the ever-increasing design complexity and how this is implemented in the software. He reviews one of Stata’s strongest features, which is its programming ability. He also examines post hoc tests as well as Stata’s graphing capabilities. The final chapters provide information on regression analysis, data transformations, and the analyses of non-parametric data.
Many agricultural researchers are unprepared for the statistics they will need to use in their profession. Written in an easy-to-read format with screen shots and illustrations, the book is suitable for a wide audience, including beginners in statistics who are new to Stata, as well as more advanced Stata users and those interested in more complex designs.
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
General Statistical Packages Comparisons. Program. Data Entry. Importing Data. Manipulating Data and Formats. Descriptive Statistics. Output Formats. Experimentation Ideas. Two Sample Tests. ANOVA. Output and Meaning. Variations of One Factor ANOVA Designs. Randomized Complete Block Design. Latin Square Designs. Balanced Incomplete Block Designs. Balanced Lattice Designs. Group Balanced Block Design. Subsampling. Two and More Factors ANOVA. Split-Plot Design. Split-Block Design. Evaluation over Years or Seasons. Three Factor Design. Split-Split Plot Design. Covariance Analysis. Programming Stata. Post Hoc Tests. Planned Comparisons. Built-in Multiple Range Tests. Programming Scheffe's Test. Preparing Graphs. Graphing in Stata. Correlation and Regression. Correlation. Linear Regression. Data Transformations. Binary, Ordinal, and Categorical Data Analysis. References. Appendix. Index.