"Native Land Digital is a Canadian not-for-profit organization, incorporated in December 2018. Native Land Digital is Indigenous-led, with an Indigenous Executive Director and Board of Directors who oversee and direct the organization. [...] Maps potentially function as colonial artifacts and represent a very particular way of seeing the world – a way primarily concerned with ownership, exclusivity, and power relations."
"The information system PANGAEA is operated as an Open Access library aimed at archiving, publishing and distributing georeferenced data from earth system research. The system guarantees long-term availability of its content through a commitment of the hosting institutions."
"Our Mission: To increase awareness and understanding of living nature through an Encyclopedia of Life that gathers, generates, and shares knowledge in an open, freely accessible and trusted digital resource."
"This information has been meticulously sourced from the three largest, most comprehensive and impartial crowdsourced databases on police killings in the country: FatalEncounters.org, the U.S. Police Shootings Database and KilledbyPolice.net. We've also done extensive original research to further improve the quality and completeness of the data; searching social media, obituaries, criminal records databases, police reports and other sources to identify the race of 90 percent of all victims in the database." Provides map and infographics as well as raw data download as spreadsheet.
"Although many of the techniques are relevant to molecular bioinformatics, the motivation for the text is much broader, focusing on topics and techniques that are applicable to a range of scientific endeavors."
Call Number: QA76.73.P98 V365 2016 (Youngblood Energy Library)
Publication Date: 2016
"For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all--IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. "
"Python Data Analytics will help you tackle the world of data acquisition and analysis using the power of the Python language. At the heart of this book lies the coverage of pandas, an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language. "
Call Number: GF 21 .Q83 2016 (Bizzell Reserves, National Weather Center stacks)
Publication Date: 2016
"Using a unique "how-to" approach to focus on the practical application of research in human geography by providing real-world examples of research methods at work in case studies, this fourth edition teaches students how to plan, execute, interpret, and effectively communicate qualitative research."
"Shows how empirical details of qualitative research can be linked to the broader social, theoretical, political, and policy concerns of qualitative geographers and the communities within which they work."
"The author's central purpose is to show inexperienced researchers how to design, collect, and analyze data and then present their results to the scientific community, while stressing the importance of ethics in research and taking the time to properly design and think through any research endeavor."
"This how-to guide covers the mechanics of data collection for applied qualitative research. It is appropriate for novice and experienced researchers alike. It can be used as both a training tool and a daily reference manual for field team members. The question and answer format and modular design make it easy for readers to find information on a particular topic quickly."
"Leads readers through framing the project and undertaking the initial bracketing interview to conducting phenomenological interviews with participants, interpreting texts, thematizing, and developing thematic structure. Rounding out discussion of the research procedures is a full chapter devoted to writing the research report. The book concludes with a section answering common questions about this style of phenomenological research."
Call Number: BF 76.5 .A95 2003 (Also available online)
Publication Date: 2003
"Meant for the novice researcher who needs guidance on what specifically to do when faced with a sea of information. It takes readers through the qualitative research process, beginning with an examination of the basic philosophy of qualitative research, and ending with planning and carrying out a qualitative research study."
"Provides an excellent introduction to the methodology and implementation of experimentation in the natural, engineering and medical sciences. [...] This book focuses on general research skills, such as adopting a scientific mindset, learning how to plan meaningful experiments and understanding the fundamentals of collecting and interpreting data. It is directed to anyone engaged in experiments." Particularly suitable for undergraduates or other novice researchers learning about designing their own experiments.
"The tools to choose the graphs and statistics that are suitable for your data, and to understand what the statistical results actually mean." A very short introduction to statistics and why you need to use them. It also includes some guidance on gathering data, focused for the social sciences, but the principles are broadly applicable.
"Studiously avoids the recipe-book style and keeps algebraic details of specific statistical methods to the minimum extent necessary to understand the underlying concepts." Recommended if you are considering designing an experiment but want a broad overview before choosing an approach, or if you have an approach but want to understand how it fits into the broader statistical and scientific thought process. The text is organized around case studies for different methods. It will likely be most applicable for undergraduates or graduate students learning about experimental design and who are comfortable with seeing equations scattered throughout the text.
This open and free introductory statistics textbook covers topics typical for a college-level non-math majors statistics course. Topics include distributions, probability, research design, estimation, hypothesis testing, power and effect size, comparison of means, regression, analysis of variance (ANOVA), transformations, chi square, and non-parametric (distribution-free) tests). It is available as a pdf, online, or as an epub. An Instructor's Manual and PowerPoint slides are also available upon request from the project leader at Rice University.
A free and open introductory statistics textbook for non-math majors. "They have sought to present only the core concepts and use a wide-ranging set of exercises for each concept to drive comprehension. [...] a smaller and less intimidating textbook that trades some extended and unnecessary topics for a better-focused presentation of the central material." It covers descriptive statistics, probability, distributions, discrete and continuous random variables, estimation, hypothesis testing, comparison of means, correlation and regression, chi square, and F-tests.
"We hope readers will take away three ideas from this book in addition to forming a foundation of statistical thinking and methods. (1) Statistics is an applied field with a wide range of practical applications. (2) You don't have to be a math guru to learn from interesting, real data. (3) Data are messy, and statistical tools are imperfect. However, when you understand the strengths and weaknesses of these tools, you can use them to learn interesting things about the world." This free and open introductory statistics textbook for non-math majors discusses data and data collection, foundations for inference with randomization and simulations (then leading into standard parametric statistics), inference with categorical and numerical data, and linear, multiple logistic regression. An introduction to probability is included as an appendix.
"An invaluable reference tool that guides readers through drafting the results of quantitative experiments." This book gives social science examples but should be of use to learners and researchers in many scientific fields in learning how to report the results of statistical tests.
"The philosophy of model-based data analysis and strategy for the analysis of empirical data. The book introduces information theoretic approaches and focuses critical attention on a priori modeling and the selection of a good approximating model that best represents the inference supported by the data. [...] The text has been written for biologists and statisticians using models for making inferences from empirical data."
"Provides advanced undergraduate as well as graduate students with a timely and comprehensive introduction to today's most commonly encountered statistical and multivariate techniques, while assuming only a limited knowledge of higher-level mathematics." Covers SPSS and SAS code; also available on Reserves at Bizzell Memorial Library.
"Reference tool covering statistics, probability theory, biostatistics, quality control, and economics with emphasis in applications of statistical methods in sociology, engineering, computer science, biomedicine, psychology, survey methodology, and other client disciplines." A good source for topics less often covered in the general textbooks.
"More than 500 entries include definitions, history, mathematical details, limitations, examples, references, and further readings. All entries include cross-references as well as the key citations. The back matter includes a timeline of statistical inventions." Another good resource for topics not included in the general texts listed previously.
Data Observation Network for Earth (DataONE) is the foundation of new innovative environmental science through a distributed framework and sustainable cyberinfrastructure that meets the needs of science and society for open, persistent, robust, and secure access to well-described and easily discovered Earth observational data.
The NIEHS Environmental Genome Project is a multi-disciplinary, collaborative effort focused on examining the relationships between environmental exposures, inter-individual sequence variation in human genes and disease risk in U.S. populations.