This book presents University of Maryland student research related to Grand Challenges and psychology. Present topics primarily address global health grand challenges, but we expect it to expand as the research included in this book expands and evolves. Each research project presented in this book was pre-registered and has an Open Science Foundation project which allows public access to the research pre-registration, materials, data, analysis code, and poster. Topics covered include psychological grit, risk-taking behavior, optimism, and motivation.

This resource was created at the University of Maryland (UMD) for instructors who want to develop open educational textbook resources. You may use this template and modify the text and format to fit your open educational resources (OER) needs, whether that is a complete textbook or a single chapter of information. The purpose of this resource is to provide a flexible and free resource for instructors that can promote and facilitate the creation and use of open educational resources.

We teach open science and have used this template to create an OER introduction to statistics textbook (Numbers don't lie (but people do), https://sites.google.com/umd.edu/statisticsinsocialsciences/home), an OER R textbook (Learning R the EZ way, https://sites.google.com/umd.edu/ezlearning-r/home), and an undergraduate research dissemination textbook (Addressing Grand Challenges through open science research, https://sites.google.com/umd.edu/umd-open-science-research/home?authuser=0). We hope others will find this resource useful as well.

This resource was created at the University of Maryland (UMD) for instructors who want to teach, students (and instructors) who want to learn, and researchers who want to use R for statistical discovery and analysis. While this is a textbook, it is largely based on hands-on examples with video walk-throughs to take you through accessing R and RStudio, the basics of R and progressing to analyses with step by step templates and video support. The goal is to build confidence with programming early on and demonstrate best coding practices from the start.

This resource was created for Introduction to Statistics students at the University of Maryland, and is designed to help you explore psychological theory, research, and practical applications of statistics. After completing this course in psychology, you will be able to:

- Explain how to use and interpret descriptive and inferential statistics in an ethically responsible way.
- Describe the difference between descriptive (central tendency, dispersion, correlation) and inferential statistics (single, multiple, logistic), and know when to use each.
- Demonstrate analytical skills by critiquing research and media claims.
- Apply statistical concepts and methods in a way that improves your own academic, personal, and professional life.

Each module is structured around key prompts - Learning Objective Questions - and followed by the links to articles, videos, and interactive demonstrations you will need to answer those questions. After studying the readings, videos, and presentations you should be able to answer the learning objective questions in detail without any notes in front of you. If you practice doing that regularly, you are well prepared for any assessment that your instructor can give you!