This activity engages learners in exploring the impact of climate change on arctic sea ice in the Bering Sea. They graph and analyze sea ice extent data, conduct a lab on thermal expansion of water, and then observe how a scientist collects long-term data on a bird population.

Students are introduced to the "Walk the Line" challenge question. They write journal responses to the question and brainstorm what information they need to answer the question. Ideas are shared with the class (or in pairs and then to the class, if class size is large). Then students read an interview with an engineer to gain a professional perspective on linear data sets and best-fit lines. Students brainstorm for additional ideas and add them to the list. With the teacher's guidance, students organize the ideas into logical categories of needed knowledge.

This activity engages students in the analysis of climate data to first find areas in the southern United States that are now close to having conditions in which the malaria parasite and its mosquito hosts thrive and then attempt to forecast when areas might become climatically suitable.

We help students see the connection between college level chemistry course work and their differential equations coursework. We do this through modeling kinetics, or rates of chemical reaction. We offer many opportunities to model these chemical reactions with data, some of which comes from traditional introductory chemistry textbooks. We ask students to verify their model through parameter estimation. We use Excel’s Trendline addition to graphs/charts to select the models for the data and transformed data to take advantage of Trendline’s set function choices and we also use Mathematica’s direct nonlinear fitting capabilities.

Breaking Continuous Flash Suppression (bCFS) has been adopted as an appealing means to study human visual awareness, but the literature is beclouded by inconsistent and contradictory results. Although previous reviews have focused chiefly on design pitfalls and instances of false reasoning, we show in this study that the choice of analysis pathway can have severe effects on the statistical output when applied to bCFS data. Using a representative dataset designed to address a specific controversy in the realm of language processing under bCFS, namely whether psycholinguistic variables affect access to awareness, we present a range of analysis methods based on real instances in the published literature, and indicate how each approach affects the perceived outcome. We provide a summary of published bCFS studies indicating the use of data transformation and trimming, and highlight that more compelling analysis methods are sparsely used in this field. We discuss potential interpretations based on both classical and more complex analyses, to highlight how these differ. We conclude that an adherence to openly available data and analysis pathways could provide a great benefit to this field, so that conclusions can be tested against multiple analyses as standard practices are updated.

Introduction to citations as a presentation. Citing data and code as well as getting citations for data and code.

Students will be asked to identify claims, evidence in warrants in a non-fiction essay.

As if they are environmental engineers, student pairs are challenged to use Google Earth Pro (free) GIS software to view and examine past data on hurricanes and tornados in order to (hypothetically) advise their state government on how to proceed with its next-year budget—to answer the question: should we reduce funding for natural disaster relief? To do this, students learn about maps, geographic information systems (GIS) and the global positioning system (GPS), and how they are used to deepen the way maps are used to examine and analyze data. Then they put their knowledge to work by using the GIS software to explore historical severe storm (tornado, hurricane) data in depth. Student pairs confer with other teams, conduct Internet research on specific storms and conclude by presenting their recommendations to the class. Students gain practice and perspective on making evidence-based decisions. A slide presentation as well as a student worksheet with instructions and questions are provided.

In this activity, students collect data and analyze the cost of using energy in their homes and investigate one method of reducing energy use. This activity provides educators and students with the means to connect 'energy use consequences' and 'climate change causes.' Through examining home energy use and calculating both pollution caused by the generation of electricity and potential savings, students can internalize these issues and share information with their families.

     This is a pathfinder designed for users who are new to Tableau Desktop and Tableau Public.  The purpose of this pathfinder is to be a companion resource to the February 25, 2023 presentation Create Accurately and Interactive Dashboards with Tableau.  The Tableau Student Ambassador presenters of the workshop were Taiwo Adegite, Junior Analyst; and Zena Patton, Corporate Learning Professional, and Librarian.  To learn more about the Tableau Community Leader Ambassador program, go to the following link  https://www.tableau.com/community/community-leaders/ambassadors      This companion resource is an artifact of a global, collaborative effort between Taiwo Adegite (Nigeria), Junior Analyst; and Zena Patton (United States of America), Corporate Learning Professional, and Librarian.Last update April 15, 2023.  This update includes resources from Flip the Tableau! Learning Experience.   

In this lesson, students will collect data about an observation that can be made in the outdoor classroom, record the data on a table, and compare the numbers collected by writing greater-than, less-than statements.

Clinical trial registries can improve the validity of trial results by facilitating comparisons between prospectively planned and reported outcomes. Previous reports on the frequency of planned and reported outcome inconsistencies have reported widely discrepant results. It is unknown whether these discrepancies are due to differences between the included trials, or to methodological differences between studies. We aimed to systematically review the prevalence and nature of discrepancies between registered and published outcomes among clinical trials. Methods We searched MEDLINE via PubMed, EMBASE, and CINAHL, and checked references of included publications to identify studies that compared trial outcomes as documented in a publicly accessible clinical trials registry with published trial outcomes. Two authors independently selected eligible studies and performed data extraction. We present summary data rather than pooled analyses owing to methodological heterogeneity among the included studies. Results Twenty-seven studies were eligible for inclusion. The overall risk of bias among included studies was moderate to high. These studies assessed outcome agreement for a median of 65 individual trials (interquartile range [IQR] 25–110). The median proportion of trials with an identified discrepancy between the registered and published primary outcome was 31 %; substantial variability in the prevalence of these primary outcome discrepancies was observed among the included studies (range 0 % (0/66) to 100 % (1/1), IQR 17–45 %). We found less variability within the subset of studies that assessed the agreement between prospectively registered outcomes and published outcomes, among which the median observed discrepancy rate was 41 % (range 30 % (13/43) to 100 % (1/1), IQR 33–48 %). The nature of observed primary outcome discrepancies also varied substantially between included studies. Among the studies providing detailed descriptions of these outcome discrepancies, a median of 13 % of trials introduced a new, unregistered outcome in the published manuscript (IQR 5–16 %). Conclusions Discrepancies between registered and published outcomes of clinical trials are common regardless of funding mechanism or the journals in which they are published. Consistent reporting of prospectively defined outcomes and consistent utilization of registry data during the peer review process may improve the validity of clinical trial publications.

In EARTH 801, you will develop skills in a programming language designed for visual arts and visualization while exploring Earth science topics. Specifically, you'll learn and practice digital graphics capabilities in order to render Earth science concepts that are otherwise difficult to visualize due to complicated space and time scales. Here, you will interact with large, open, freely-available data sets by collecting, plotting, and analyzing them using a variety of computational methods. You'll be ready to teach secondary school students a range of Next Generation Science Standard skills involving data collecting, manipulation, analysis, and plotting. You'll also read and discuss current research regarding the teaching, learning, and evaluation of visualization skills, as well as multiple external representations of science concepts.

The issue of confounding is of central importance in any analytic epidemiological study (as well as in those descriptive studies aiming to compare different populations), especially in the case of observational studies. Confounding results from non-random differences between the groups of animals being compared in relation to a second, 'confounding' exposure which is independently associated with both the exposure of interest (although not a consequence of this) and the outcome of interest (although not an effect of this). This results in the effect of the exposure of interest is 'mixed up' with the effect of the confounding exposure, and therefore an incorrect estimate of the true association. As such, confounding is viewed by many authors as a form of bias - however, unlike forms of selection and information bias, it is a natural feature of the data (in the case of an observational study), and techniques are available to account for it during analysis.

This webinar (recorded Sept. 27, 2017) introduces how to connect other services as add-ons to projects on the Open Science Framework (OSF; https://osf.io). Connecting services to your OSF projects via add-ons enables you to pull together the different parts of your research efforts without having to switch away from tools and workflows you wish to continue using. The OSF is a free, open source web application built to help researchers manage their workflows. The OSF is part collaboration tool, part version control software, and part data archive. The OSF connects to popular tools researchers already use, like Dropbox, Box, Github and Mendeley, to streamline workflows and increase efficiency.

This video will go over three issues that can arise when scientific studies have low statistical power. All materials shown in the video, as well as the content from our other videos, can be found here: https://osf.io/7gqsi/

The students discover the basics of heat transfer in this activity by constructing a constant pressure calorimeter to determine the heat of solution of potassium chloride in water. They first predict the amount of heat consumed by the reaction using analytical techniques. Then they calculate the specific heat of water using tabulated data, and use this information to predict the temperature change. Next, the students will design and build a calorimeter and then determine its specific heat. After determining the predicted heat lost to the device, students will test the heat of solution. The heat given off by the reaction can be calculated from the change in temperature of the water using an equation of heat transfer. They will compare this with the value they predicted with their calculations, and then finish by discussing the error and its sources, and identifying how to improve their design to minimize these errors.

This lesson demonstrates how easy it is to create a binary FRED map. Students search for state-level data on average weekly earnings and visualize them in FRED. The goals are for students to customize a map, observe patterns in mapped data, and note differences across geographical areas.

Students learn about viscoelastic material behavior, such as strain rate dependence and creep, by using silly putty, an easy-to-make polymer material. They learn how to make silly putty, observe its behavior with different strain rates, and then measure the creep time of different formulations of silly putty. By seeing the viscoelastic behavior of silly putty, students start to gain an understanding of how biological materials function. Students gain experience in data collection, graph interpretation, and comparison of material properties to elucidate material behavior. It is recommended that students perform Part 1of the activity first (making and playing with silly putty), then receive the content and concept information in the associated lesson, and then complete Part 2 of the activity (experimenting and making measurements with silly putty).