### Goals of this book

The goal of this book is to introduce to students interested in extension education, outreach, and public education to the quantitative methods used to assess the evaluation of these activities. Extension education includes a diverse collection of subject matter, including environmental science, home horticulture, agriculture, youth development, nutrition, and financial literacy.

Tools for evaluating educational programs may include in-class surveys that measure the knowledge gain of students in a course or follow-up surveys to determine the behaviors adopted by course participants. Evaluation may also include any number of measured variables, perhaps the age of youth participants, the number of calories eaten daily by students in a nutrition program, or the organic matter content of farm fields managed by participating farmers.

The examples and methods here are chosen specifically to be applicable to the evaluation of extension education programs. That being said, these methods are some of the most common used in the analysis of experiments—techniques used from diverse disciplines from manufacturing to environmental science to psychology, though each of these disciplines has additional methods used in specific situations.

### Specific learning goals

One goal of this book is to give
readers the skills and
abilities to be able to understand the graphs and statistics that you
might
encounter in a publication such as the *Journal of Extension*
or other
academic reports of program results. As examples, students
will be able to
answer the questions: *What can I conclude from this bar plot?*
*How do
I interpret this *p*-value? * *What
is an *r-squared* value?*

A second goal is for readers to be
able to design and
analyze their own program evaluation experiments in order to document
the
impacts of their extension teaching or research. *What
analysis would I use
to assess knowledge gain with before-and-after surveys?*
*What statistics
should I report to convey the results of this analysis?*
*Can I explain
the results with a graph?*

### Pre-requisites

This book is written for students at the undergraduate level with no prior knowledge of the analysis of experiments, and with no prior knowledge of computer programming. This being said, students with no background in these areas will need to apply care and dedication in order to understand the material and the computer code used in examples. These students may also need to explore the optional readings to obtain a better foundation in statistical thinking and theory.

### What this book will not cover

#### Designing and conducting surveys

There are many skills and considerations that go into conducting competent assessments of education programs. This book will not cover these many of these topics in any depth. For example, good survey design and effective survey questions will be touched on only very briefly. Conducting surveys well, for example by avoiding sampling bias, will also not be covered in any significant way.

#### Advanced statistical analyses

There are variety of relatively advanced statistical analyses that are used in even relatively simple studies. This book focuses on only the most basic analyses for common designs used in extension evaluation. A solid understanding of these analyses will give the reader the foundation for exploring more complicated analyses as the student wishes or the situation calls for.

#### R programming

R is a flexible and powerful programming language. Readers
of this book will benefit from learning the basics of programming in R;
however, descriptions of R programming will be kept to a minimum here. There
are books and online resources available to learn R programming. A few places
to start include the book by Roger Peng listed in the “R programming” section
and the courses offered by the resources listed in “Online Learning Modules and
Massive Open Online Courses (MOOC’s)” section in the *Statistics Textbooks
and Other Resources* chapter.