Agricultural Statistical Data Analysis Using Stata

Practical statistics is a powerful tool used frequently by agricultural researchers and graduate students involved in investigating experimental design and analysis. One of the most widely used statistical analysis software packages for this purpose is Stata. The Stata software program has matured into a user-friendly environment with a wide variety of statistical functions. Agricultural Statistical Data Analysis Using Stata introduces readers to the use of Stata to solve agricultural statistical problems. 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.

General Statistical Packages Comparisons Program Windows and Menus What’s on the Menu? Data Entry Importing Data Manipulating Data and Formats Descriptive Statistics Output FormatsExperimentation IdeasTwo Sample Tests ANOVA Output and Meaning Variations of One Factor ANOVA Designs Randomized Complete Block Design Latin Square DesignsBalanced 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 SeasonsThree Factor Design Split-Split Plot Design Covariance AnalysisProgramming Stata Post Hoc Tests Planned Comparisons Built-in Multiple Range Tests Programming Scheffé’s Test Preparing GraphsGraphing in StataCorrelation and Regression Correlation Linear Regression Data TransformationsBinary, Ordinal, and Categorical Data Analysis References Appendix Index

George Boyhan, PhD, is a professor of horticulture and an extension vegetable specialist. He has worked for 15 years at the University of Georgia in this capacity and has conducted a wide variety of experiments requiring statistical analyses. Prior to this, he worked at Auburn University as a senior research associate, where he designed experiments, collected data, and analyzed results. Dr. Boyhan has worked with a wide variety of crops in his career. He currently studies the development of disease-resistant pumpkins, develops watermelon varieties for organic production, and evaluates sustainable production practices. Dr. Boyhan is an internationally recognized authority on vegetable production and has given presentations at a number of venues both in the United States and internationally. He has published two book chapters, over 40 referred publications, and many other publications on vegetable production and culture.