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.
Table of Contents
General Statistical Packages Comparisons
Windows and Menus
What’s on the Menu?
Manipulating Data and Formats
Two Sample Tests
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
Two and More Factors ANOVA
Evaluation over Years or Seasons
Three Factor Design
Split-Split Plot Design
Post Hoc Tests
Built-in Multiple Range Tests
Programming Scheffé’s Test
Graphing in Stata
Correlation and Regression
Binary, Ordinal, and Categorical Data Analysis
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.