## 1.1 Resources

This course is unlike any you have likely encountered in that you will be driving the content and direction of your own learning. In many ways we will be asking more from you than any other introductory course ever has. To support you in this challenge, there are a number of useful resources.

This Book: This book integrates the applied steps of a research project with the basic knowledge needed to meaningfully engage in quantitative research. Much of the background on descriptive and inferential statistics has been drawn from the Open Learning Initiative, a not-for-profit educational project aimed at transforming instruction and improving learning outcomes for students.

Empowerment Through Statistical Computing: While there is widespread agreement that introductory students need to learn statistical programming, opinions differ widely both within and across disciplines about the specific statistical software program that should be used. While many introductory statistics courses cover the practical aspects of using a single software package, our focus will be more generally on computing as a skill that will expand your capacity for statistical application and for engaging in deeper levels of quantitative reasoning. Instead of providing “canned” exercises for you to repeat, you will be provided with flexible syntax for achieving a host of data management and analytic tasks in the pursuit of answers to questions of greatest interest to you. Most importantly, syntax for R will be presented in the context of each step of the research process.

Loads of Support: Through the in-class workshop sessions and peer group exchanges, a great deal of individualized support will be available to you. Taking advantage of this large amount of support means that you are succeeding in making the most of your experience in this course.