Phoebis philea: Information
To develop an understanding of modern industrial technologies that clean up and prevent air pollution, students build and observe a variety of simple models of engineering pollutant recovery methods: scrubber, electrostatic precipitator, cyclone and baghouse. In an associated literacy activity, students become more aware of global environmental problems and play a part in their solution by writing environmental action campaign letters.
The applets in this section of Statistical Java address Power. Users can perform one or two tailed tests for proportions or means for one or two samples. Set the parameters and drag the mouse across the graph to see how effect size affects power.
Just a blog on power of words
Practical Considerations for Navigating Registered Reports
In this activity, students investigate soil erosion and how a changing climate could influence erosion rates in agricultural areas. This activity is part of a larger InTeGrate module called Growing Concern.
Designed to meet the scope and sequence of your course, Principles of Finance provides a strong foundation in financial applications using an innovative use-case approach to explore their role in business decision-making. An array of financial calculator and downloadable Microsoft Excel data exercises also engage students in experiential learning throughout. With flexible integration of technical instruction and data, this title prepares students for current practice and continual evolution.
Principles of Management is designed to meet the scope and sequence requirements of the introductory course on management. This is a traditional approach to management using the leading, planning, organizing, and controlling approach. Management is a broad business discipline, and the Principles of Management course covers many management areas such as human resource management and strategic management, as well behavioral areas such as motivation. No one individual can be an expert in all areas of management, so an additional benefit of this text is that specialists in a variety of areas have authored individual chapters.
14. Brave New World: Privacy, Data Sharing and Evidence Based Policy Making
The trifecta of globalization, urbanization and digitization have created new opportunities and challenges across our nation, cities, boroughs and urban centers. Cities in particular are in a unique position at the center of commerce and technology becoming hubs for innovation and practical application of emerging technology. In this rapidly changing 24/7 digitized world, governments are leveraging innovation and technology to become more effective, efficient, transparent and to be able to better plan for and anticipate the needs of its citizens, businesses and community organizations. This class will provide the framework for how cities and communities can become smarter and more accessible with technology and more connected.
This page of Statistical Java describes 11 different probability distributions including the Binomial, Poisson, Negative Binomial, Geometric, T, Chi-squared, Gamma, Weibull, Log-Normal, Beta, and F. Each distribution has its own applet.
Product liability refers to a manufacturer or seller being held liable for placing a defective product into the hands of a consumer. Responsibility for a product defect that causes injury lies with all sellers of the product who are in the distribution chain.
Neste documento estão contidos os produtos elaborados pelos participantes da pesquisa científica intitulada "Aprendizagem Baseada em Projetos na investigação dos serviços ecossistêmicos dos manguezais em Estância-SE" realizada pela acadêmica do Programa de Pós-Graduação em Rede Nacional para Ensino das Ciências Ambientais (PROFCIAMB) associada UFS, pela mestranda Camila Silva Ramos, orientada pela professora Dra. Sindiany Suelen Caduda dos Santos e coorientada pela professora Dra. Maria do Socorro Ferreira da Silva, entre os anos de 2020 a 2022.O documento apresenta portfólios e artefatos que foram elaborados em tempos de pandemia da COVID-19, durante o processo de ensino e aprendizagem com uso da metodologia ativa Aprendizagem Baseada em Projetos (ABP), no período do ensino remoto emergencial, de modo a atender as normas de biossegurança determinadas pelo governo brasileiro e do estado de Sergipe.
Data Carpentry Genomics workshop lesson to learn how to structure your metadata, organize and document your genomics data and bioinformatics workflow, and access data on the NCBI sequence read archive (SRA) database. Good data organization is the foundation of any research project. It not only sets you up well for an analysis, but it also makes it easier to come back to the project later and share with collaborators, including your most important collaborator - future you. Organizing a project that includes sequencing involves many components. There’s the experimental setup and conditions metadata, measurements of experimental parameters, sequencing preparation and sample information, the sequences themselves and the files and workflow of any bioinformatics analysis. So much of the information of a sequencing project is digital, and we need to keep track of our digital records in the same way we have a lab notebook and sample freezer. In this lesson, we’ll go through the project organization and documentation that will make an efficient bioinformatics workflow possible. Not only will this make you a more effective bioinformatics researcher, it also prepares your data and project for publication, as grant agencies and publishers increasingly require this information. In this lesson, we’ll be using data from a study of experimental evolution using E. coli. More information about this dataset is available here. In this study there are several types of files: Spreadsheet data from the experiment that tracks the strains and their phenotype over time Spreadsheet data with information on the samples that were sequenced - the names of the samples, how they were prepared and the sequencing conditions The sequence data Throughout the analysis, we’ll also generate files from the steps in the bioinformatics pipeline and documentation on the tools and parameters that we used. In this lesson you will learn: How to structure your metadata, tabular data and information about the experiment. The metadata is the information about the experiment and the samples you’re sequencing. How to prepare for, understand, organize and store the sequencing data that comes back from the sequencing center How to access and download publicly available data that may need to be used in your bioinformatics analysis The concepts of organizing the files and documenting the workflow of your bioinformatics analysis
Students experience the steps of the engineering design process as they design solutions for a real-world problem that could affect their health. After a quick review of the treatment processes that municipal water goes through before it comes from the tap, they learn about the still-present measurable contamination of drinking water due to anthropogenic (human-made) chemicals. Substances such as prescription medication, pesticides and hormones are detected in the drinking water supplies of American and European metropolitan cities. Using chlorine as a proxy for estrogen and other drugs found in water, student groups design and test prototype devices that remove the contamination as efficiently and effectively as possible. They use plastic tubing and assorted materials such as activated carbon, cotton balls, felt and cloth to create filters with the capability to regulate water flow to optimize the cleaning effect. They use water quality test strips to assess their success and redesign for improvement. They conclude by writing comprehensive summary design reports.
This will provide a basic understanding of the concept Pythagoras theorem and its application.The given video tutorial are awesome which will increase your knowledge a lot.
A survey in the United States revealed that an alarmingly large percentage of university psychologists admitted having used questionable research practices that can contaminate the research literature with false positive and biased findings. We conducted a replication of this study among Italian research psychologists to investigate whether these findings generalize to other countries. All the original materials were translated into Italian, and members of the Italian Association of Psychology were invited to participate via an online survey. The percentages of Italian psychologists who admitted to having used ten questionable research practices were similar to the results obtained in the United States although there were small but significant differences in self-admission rates for some QRPs. Nearly all researchers (88%) admitted using at least one of the practices, and researchers generally considered a practice possibly defensible if they admitted using it, but Italian researchers were much less likely than US researchers to consider a practice defensible. Participants’ estimates of the percentage of researchers who have used these practices were greater than the self-admission rates, and participants estimated that researchers would be unlikely to admit it. In written responses, participants argued that some of these practices are not questionable and they have used some practices because reviewers and journals demand it. The similarity of results obtained in the United States, this study, and a related study conducted in Germany suggest that adoption of these practices is an international phenomenon and is likely due to systemic features of the international research and publication processes.
Students explore the physical science behind the causes of quicksand and become familiar with relationship between concepts such as total stress, pore pressure, and effective stress. Students also relate these concepts to soil liquefaction—a major concern during earthquakes. Students begin the activity by designing a simple device to test the effects of quicksand on materials of different densities and weights. They prototype a support structure that works to prevent a heavy object from sinking into quicksand. At the end of the activity, students reflect on the engineering design process and consider the steps civil engineers take in designing sturdy buildings and other structures.
The analysis of longitudinal observational data can take many forms and requires many decisions, with research findings and conclusions often found to differ across independent longitudinal studies addressing the same question. Differences in measurements, sample composition (e.g., age, cohort, country/culture), and statistical models (e.g., change/time function, covariate set, centering, treatment of incomplete data) can affect the replicability of results. The central aim of the Integrative Analysis of Longitudinal Studies of Aging (IALSA) research network (NIH/NIA P01AG043362) is to optimize opportunities for replication and cross-validation across heterogeneous sources of longitudinal data by evaluating comparable conceptual and statistical models at the construct-level. We will provide an overview of the methodological challenges associated with comparative longitudinal and international research, including the comparability of alternative models of change, measurement harmonization and construct-level comparison, retest effects, distinguishing and contrasting between-person and within-person effects across studies, and evaluation of alternative models for change over time. These methodological challenges and recommended approaches will be discussed within the context of reproducible and replication research focused on longitudinal studies.
Short Description:
The purpose of this OER is to provide students with a comprehensive textbook aligned with the NDT 130 (Radiographic Testing) course as taught at Linn-Benton Community College. See the bottom of each page for downloadable Spanish translation. Order a print copy: http://www.lulu.com/content/paperback-book/radiation-safety/26088192
Long Description:
Radiation Safety (NDT 130) is the first in a series of Industrial Radiographic Testing classes taught at Linn Benton Community College (LBCC) in Albany, Oregon. 40 hours of Radiation Safety training is required of any individual working with x-ray and Gamma radiation sources in industrial radiographic testing, including industrial radiographic inspection students. NDT 130 is part of LBCC’s two-year Associate of Applied Science program in Non-Destructive Testing (NDT). The purpose of this OER is to provide students with a comprehensive textbook aligned with the NDT 130 course as taught at LBCC. NDT 130 is taught in accordance with ASNT, SNT TC-1A recommended practice and topical outline following ANSI/ASNT CP-105 2016 guidelines (page 63) for Basic Radiographic Physics Course and Appendix A (pages 113-114) for Radiation Safety topical outline.
The OER is organized so each unit represents approximately a week in our term and includes printable Word documents at the end of each Unit section. Included at the conclusion of each section is a Spanish translation in a printable Word File.
Order a print copy: http://www.lulu.com/content/paperback-book/radiation-safety/26088192
Word Count: 17921
ISBN: 978-1-63635-021-9
(Note: This resource's metadata has been created automatically by reformatting and/or combining the information that the author initially provided as part of a bulk import process.)
Hypothesizing after the results are known (HARK) has been disparaged as data dredging, and safeguards including hypothesis preregistration and statistically rigorous oversight have been recommended. Despite potential drawbacks, HARK has deepened thinking about complex causal processes. Some of the HARK precautions can conflict with the modern reality of researchers’ obligations to use big, ‘organic’ data sources—from high-throughput genomics to social media streams. We here propose a HARK-solid, reproducible inference framework suitable for big data, based on models that represent formalization of hypotheses. Reproducibility is attained by employing two levels of model validation: internal (relative to data collated around hypotheses) and external (independent to the hypotheses used to generate data or to the data used to generate hypotheses). With a model-centered paradigm, the reproducibility focus changes from the ability of others to reproduce both data and specific inferences from a study to the ability to evaluate models as representation of reality. Validation underpins ‘natural selection’ in a knowledge base maintained by the scientific community. The community itself is thereby supported to be more productive in generating and critically evaluating theories that integrate wider, complex systems.