Short Description:
Psychology research methods readings for students enrolled in PSY 321 at Portland State University

Word Count: 129140

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In this task sutdents use a dotplot, histogram or boxplot to summarize data.

P values represent a widely used, but pervasively misunderstood and fiercely contested method of scientific inference. Display items, such as figures and tables, often containing the main results, are an important source of P values. We conducted a survey comparing the overall use of P values and the occurrence of significant P values in display items of a sample of articles in the three top multidisciplinary journals (Nature, Science, PNAS) in 2017 and, respectively, in 1997. We also examined the reporting of multiplicity corrections and its potential influence on the proportion of statistically significant P values. Our findings demonstrated substantial and growing reliance on P values in display items, with increases of 2.5 to 14.5 times in 2017 compared to 1997. The overwhelming majority of P values (94%, 95% confidence interval [CI] 92% to 96%) were statistically significant. Methods to adjust for multiplicity were almost non-existent in 1997, but reported in many articles relying on P values in 2017 (Nature 68%, Science 48%, PNAS 38%). In their absence, almost all reported P values were statistically significant (98%, 95% CI 96% to 99%). Conversely, when any multiplicity corrections were described, 88% (95% CI 82% to 93%) of reported P values were statistically significant. Use of Bayesian methods was scant (2.5%) and rarely (0.7%) articles relied exclusively on Bayesian statistics. Overall, wider appreciation of the need for multiplicity corrections is a welcome evolution, but the rapid growth of reliance on P values and implausibly high rates of reported statistical significance are worrisome.

In this activity, students will analyze raw data obtained from an experiment that explores the effect of overexpressing the Ssk protein in order to strengthen the intestinal barrier and prevent bacteria from leaking out of the gut and into the hemolymph, which is the fruit fly equivalent to blood in the circulatory system. Using Excel, students will fit an exponential function to the few known data points and will then interpolate the missing data points and extrapolate a few future data points. They will also learn how they can fit a linear model by transforming the data (applying the logarithmic function) and use that model to estimate the missing data points. This activity involves both statistical analysis and mathematical modeling as well as displaying the usefulness of mathematical models for biological data analysis.

In week one of the exercise students determine stream discharge by doing some tedious, but simple hand calculations using data sets provided by the instructor. The following week is designed to be more hands-on. Here, they collect their own field data and create a spreadsheet to perform the calculations more efficiently and accurately. By collecting the data themselves, students gain a more thorough understanding of how stream discharge is both measured and computed; they also learn how the results can be used to determine groundwater baseflow. The fact they do hand calculations prior to creating the spreadsheet helps build their math skills and reduces the "black-box" effect that often develops when using software for data analysis. Students also gain valuable experience creating spreadsheets and learn how this tool can be used to perform repetitive computations more efficiently and with less error. Finally, this exercise asks students to consider the accuracy of their replicate field measurements through a series of questions related to their standard deviation and percent error calculations.

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The four exercises give students an opportunity to use their knowledge of graphs, algebra, and maps to solve simple geological problems.

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Students analyze the interplay between science and politics on the issue of drilling for oil in the Arctic National Wildlife Refuge.

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Volume 23, Issue 2 (2022)

Short Description:
RANGE: Undergraduate Research Journal's primary goal is to make more visible the rich and diverse scholarship conducted by University of Utah undergraduates.

Long Description:
RANGE: Undergraduate Research Journal’s primary goal is to make more visible the rich and diverse scholarship conducted by University of Utah undergraduates. The journal is a publication of the University of Utah’s Undergraduate Studies Office of Undergraduate Research. The mission of the Office of Undergraduate Research (OUR) is to facilitate and promote undergraduate student-faculty collaborative research and creative works in all disciplines throughout the University of Utah campus through equitable programming, diverse representation, and social justice. https://our.utah.edu/

Word Count: 84033

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Volume 24, Issue 1

Short Description:
RANGE: Undergraduate Research Journal's primary goal is to make more visible the rich and diverse scholarship conducted by University of Utah undergraduates.

Long Description:
RANGE: Undergraduate Research Journal’s primary goal is to make more visible the rich and diverse scholarship conducted by University of Utah undergraduates. The journal is a publication of the University of Utah’s Undergraduate Studies Office of Undergraduate Research. The mission of the Office of Undergraduate Research (OUR) is to facilitate and promote undergraduate student-faculty collaborative research and creative works in all disciplines throughout the University of Utah campus through equitable programming, diverse representation, and social justice. https://our.utah.edu/

Word Count: 233549

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Students create a STELLA model of the radioactive decay process.

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This activity leads students through derivations of the equations associated with radiometric dating.

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This Computer Technology lab is designed to engage students in the process of organizing and presenting data in a visual way so that they can then summarize in writing their conclusions about the relationships between the data.

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A Guide for People with No Coding Experience

Short Description:
If you do not know where to start with R and R Studio, this short book is for you.

Long Description:
This book covers the basics of R and R Studio for people with no coding experience and no computer science background. It is for both beginner students and people whose job might require them to get into data analysis and statistics with no prior background. This is the book to get you started in understanding the logic of the R language in the R Studio environment so you can then move on to more difficult topics.

It is also part of the first unit of work for the College of Dupage courses Introduction to Data Science (Sociology 1205), and Introduction to Research Methods (Sociology 2200).

Word Count: 2862

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There are a lot of events in life that we just can’t predict, but just because something is random doesn’t mean we don’t know or can’t learn anything about it. Today, we’re going to talk about how we can extract information from seemingly random events starting with the expected value or mean of a distribution and walking through the first four “moments” - the mean, variance, skewness, and kurtosis.

This unit applies a spreadsheet, based on the storm water hydrograph modeling module, that applies the widely utilized Rational Method to estimate hydrographs and flooding for urban watersheds. The specific structure of the model is based on assumptions encoded for Maricopa County, Arizona, which is an urbanized area in the Desert Southwest of the USA, so the model is directly applicable to any similar climate. The model is broadly applicable to urban watersheds anywhere in the world, if appropriate adjustments are made to model parameters and if the necessary input data can be obtained. This model is designed to be utilized in parallel with a modeling guide by the same authors and alongside conceptual instruction in the hydrological concepts of rainfall and runoff processes in undergraduate classrooms. Hydrology and/or computational learning outcomes are assessed using a validated pre/post assessment instrument included with the unit.

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Welcome to this Quantitative Reasoning resource in Spanish. This resource can be used as an alternative to a traditional mathematics textbook for a one-semester course. It consists of free resources available to all users such as YouTube, Khan Academy in Spanish and much more. This resource is intended for Spanish-speaking students, but it does contain some resources in English which can be translated by the student as needed, or for videos in English, instructions are provided so students can view subtitles in English. 

This set of problems involves calculations of changes in radiogenic isotope ratios. It requires students to understand the concept of an isochron and how isotope ratios change (or do not change) during magma mixing and crystal fractionation.

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Use a topographic map to deliniate a watershed, draw a map bar scale, and calculate a map ratio scale.

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This is a short experimental study of what happens to aluminum hydroxide, silicic acid, magnesium oxide, and calcium carbonate (or reagents of instructors choice) when they are heated to 110 and 1200 degrees.

Students determine the formula and calculate the mole percent and weight percent of each element and oxide in each reagent.
They heat the samples and calculate percentage weight loss or gain.
Finally, they write a lab report summarizing their results.

Be sure to have students save their samples for later use in a lab that introduces X-ray diffraction.

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The inquiry method and meteorological and astronomical online data can be used to elicit the inconsistencies of students' naÃve ideas about the "real" reasons for the seasons. The first phase of this two-part investigation uses online meteorological data to identify factors that might explain differences of seasonal temperatures among cities These factors are used to hypothesize why differences of seasonal temperatures occur among cities. During the second phase, the variables and hypotheses that were previously identified in part one are used to design and conduct an inquiry-oriented investigation. Astronomical data is used as part of the investigation to "test" students' hypotheses -- conclusions are drawn then communicated.

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