As currently taught in the United States, introductory courses in analytical chemistryemphasize quantitative (and sometimes qualitative) methods of analysis along with a heavydose of equilibrium chemistry. Analytical chemistry, however, is much more than a collection ofanalytical methods and an understanding of equilibrium chemistry; it is an approach to solvingchemical problems. Although equilibrium chemistry and analytical methods are important, theircoverage should not come at the expense of other equally important topics.

The introductory course in analytical chemistry is the ideal place in the undergraduate chemistry curriculum forexploring topics such as experimental design, sampling, calibration strategies, standardization,optimization, statistics, and the validation of experimental results. Analytical methods comeand go, but best practices for designing and validating analytical methods are universal. Becausechemistry is an experimental science it is essential that all chemistry students understand theimportance of making good measurements.

My goal in preparing this textbook is to find a more appropriate balance between theoryand practice, between “classical” and “modern” analytical methods, between analyzing samplesand collecting samples and preparing them for analysis, and between analytical methods anddata analysis. There is more material here than anyone can cover in one semester; it is myhope that the diversity of topics will meet the needs of different instructors, while, perhaps,suggesting some new topics to cover.

Accumulating evidence indicates high risk of bias in preclinical animal research, questioning the scientific validity and reproducibility of published research findings. Systematic reviews found low rates of reporting of measures against risks of bias in the published literature (e.g., randomization, blinding, sample size calculation) and a correlation between low reporting rates and inflated treatment effects. That most animal research undergoes peer review or ethical review would offer the possibility to detect risks of bias at an earlier stage, before the research has been conducted. For example, in Switzerland, animal experiments are licensed based on a detailed description of the study protocol and a harm–benefit analysis. We therefore screened applications for animal experiments submitted to Swiss authorities (n = 1,277) for the rates at which the use of seven basic measures against bias (allocation concealment, blinding, randomization, sample size calculation, inclusion/exclusion criteria, primary outcome variable, and statistical analysis plan) were described and compared them with the reporting rates of the same measures in a representative sub-sample of publications (n = 50) resulting from studies described in these applications. Measures against bias were described at very low rates, ranging on average from 2.4% for statistical analysis plan to 19% for primary outcome variable in applications for animal experiments, and from 0.0% for sample size calculation to 34% for statistical analysis plan in publications from these experiments. Calculating an internal validity score (IVS) based on the proportion of the seven measures against bias, we found a weak positive correlation between the IVS of applications and that of publications (Spearman’s rho = 0.34, p = 0.014), indicating that the rates of description of these measures in applications partly predict their rates of reporting in publications. These results indicate that the authorities licensing animal experiments are lacking important information about experimental conduct that determines the scientific validity of the findings, which may be critical for the weight attributed to the benefit of the research in the harm–benefit analysis. Similar to manuscripts getting accepted for publication despite poor reporting of measures against bias, applications for animal experiments may often be approved based on implicit confidence rather than explicit evidence of scientific rigor. Our findings shed serious doubt on the current authorization procedure for animal experiments, as well as the peer-review process for scientific publications, which in the long run may undermine the credibility of research. Developing existing authorization procedures that are already in place in many countries towards a preregistration system for animal research is one promising way to reform the system. This would not only benefit the scientific validity of findings from animal experiments but also help to avoid unnecessary harm to animals for inconclusive research.

The final activity of this unit, which integrates the Keepers of the Gate unit through the Go Public challenge, involves students taking part in experimental design. They design a lab that answers the challenge question: "You are spending the night with your grandmother when your throat starts to feel sore. Your grandma tells you to gargle with salt water and it will feel much better. Thinking this is an old wive's tale, you scoff, but when you try it later that night it works! Why?" Students must have their plan approved by the instructor before they begin. A formal lab write-up is due as part of the laboratory investigation.

Two lessons and their associated activities explore cellular respiration and population growth in yeasts. Yeast cells are readily obtained and behave predictably, so they are very appropriate to use in middle school classrooms. In the first lesson, students are introduced to yeast respiration through its role in the production of bread and alcoholic beverages. A discussion of the effects of alcohol on the human body is used both as an attention-getting device, and as a means to convey important information at an impressionable age. In the associated activity, students set up a simple way to indirectly observe and quantify the amount of respiration occurring in yeast-molasses cultures. Based on questions that arise from this activity, in the second lesson students work in small groups as they design and execute their own experiments to determine how environmental factors affect yeast population growth.

As a class, students use a low-cost air quality monitor (a rentable “Pod”) to measure the emissions from different vehicles. By applying the knowledge about combustion chemistry that they gain during the pre-activity reading (or lecture presentation, alternatively), students predict how the emissions from various vehicles will differ in terms of pollutants (CO2, VOCs and NO2), and explain why. After data collection, students examine the time series plots as a class—a chance to interpret the results and compare them to their predictions. Short online videos and a current event article help to highlight the real-world necessity of understanding and improving vehicle emissions. Numerous student handouts are provided. The activity content may be presented independently of its unit and without using an air quality monitor by analyzing provided sample data.

The designing, collecting, analyzing, and reporting of psychological studies entail many choices that are often arbitrary. The opportunistic use of these so-called researcher degrees of freedom aimed at obtaining statistically significant results is problematic because it enhances the chances of false positive results and may inflate effect size estimates. In this review article, we present an extensive list of 34 degrees of freedom that researchers have in formulating hypotheses, and in designing, running, analyzing, and reporting of psychological research. The list can be used in research methods education, and as a checklist to assess the quality of preregistrations and to determine the potential for bias due to (arbitrary) choices in unregistered studies.

In the first part of the activity, each student chews a piece of gum until it loses its sweetness, and then leaves the gum to dry for several days before weighing it to determine the amount of mass lost. This mass corresponds to the amount of sugar in the gum, and can be compared to the amount stated on the package label. In the second part of the activity, students work in groups to design and conduct new experiments based on questions of their own choosing. These questions arise naturally from observations during the first experiment, and from students' own experiences with and knowledge of the many varieties of chewing and bubble gums available.

In animal experiments, animals, husbandry and test procedures are traditionally standardized to maximize test sensitivity and minimize animal use, assuming that this will also guarantee reproducibility. However, by reducing within-experiment variation, standardization may limit inference to the specific experimental conditions. Indeed, we have recently shown in mice that standardization may generate spurious results in behavioral tests, accounting for poor reproducibility, and that this can be avoided by population heterogenization through systematic variation of experimental conditions. Here, we examined whether a simple form of heterogenization effectively improves reproducibility of test results in a multi-laboratory situation. Each of six laboratories independently ordered 64 female mice of two inbred strains (C57BL/6NCrl, DBA/2NCrl) and examined them for strain differences in five commonly used behavioral tests under two different experimental designs. In the standardized design, experimental conditions were standardized as much as possible in each laboratory, while they were systematically varied with respect to the animals' test age and cage enrichment in the heterogenized design. Although heterogenization tended to improve reproducibility by increasing within-experiment variation relative to between-experiment variation, the effect was too weak to account for the large variation between laboratories. However, our findings confirm the potential of systematic heterogenization for improving reproducibility of animal experiments and highlight the need for effective and practicable heterogenization strategies.

Students will be exposed to all aspects of a cutting-edge technique in modern electrophysiology, in a highly structured, team oriented environment. The research projects will probe the neural mechanisms of learning and memory through tetrode array recordings coupled with patterned microstimulation. Due to the broad nature of tasks to be completed, coupled with the team oriented approach we will be employing, we are interested in students with a wide variety of laboratory experience and skill levels.

After investigating density, displacement, and buoyancy in hands-on experiments, students take on the role of designers to create boats for We B Toys. Students create brochures or multimedia slideshows to persuade We B Toys to consider their boat designs for a new line of toy boats.

This unit plan was originally developed by the Intel® Teach program as an exemplary unit plan demonstrating some of the best attributes of teaching with technology.

This team-taught multidisciplinary course provides information relevant to the conduct and interpretation of human brain mapping studies. It begins with in-depth coverage of the physics of image formation, mechanisms of image contrast, and the physiological basis for image signals. Parenchymal and cerebrovascular neuroanatomy and application of sophisticated structural analysis algorithms for segmentation and registration of functional data are discussed. Additional topics include: fMRI experimental design including block design, event related and exploratory data analysis methods, and building and applying statistical models for fMRI data; and human subject issues including informed consent, institutional review board requirements and safety in the high field environment.

Additional Faculty
Div Bolar
Dr. Bradford Dickerson
Dr. John Gabrieli
Dr. Doug Greve
Dr. Karl Helmer
Dr. Dara Manoach
Dr. Jason Mitchell
Dr. Christopher Moore
Dr. Vitaly Napadow
Dr. Jon Polimeni
Dr. Sonia Pujol
Dr. Bruce Rosen
Dr. Mert Sabuncu
Dr. David Salat
Dr. Robert Savoy
Dr. David Somers
Dr. A. Gregory Sorensen
Dr. Christina Triantafyllou
Dr. Wim Vanduffel
Dr. Mark Vangel
Dr. Lawrence Wald
Dr. Susan Whitfield-Gabrieli
Dr. Anastasia Yendiki

Examination of experimental design as applied to nutrition research, including intervention, observational, survey, and animal models. Development of research topics; methods of data collection; interpretation and presentation of results; ethical considerations; application of principles for development of research proposals and evaluation of the nutrition literature. (Prerequisites: advanced coursework in Nutrition and a course in Biostatistics)

This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:

"Host-microbiome interactions are a critical component of host health, and plants have a particularly complex relationship with their microbiomes. Understanding these functional relationships will allow us to predict, and even influence, host fitness. Many ‘-omics’ techniques have been developed, and each is a powerful tool solo, but combining them opens the door to a more holistic, systems-level understanding. This strategy, called holo-omics, requires careful experimental design and faces several challenges as a field. First, it currently lacks well-tested analytical frameworks. Second, there is a need for freely available, specialized bioinformatics tools, as most focus on just one data source and don't integrate host and microbe data. Lastly, the heterogeneous nature of holo-omics data requires a wide range of expertise - including plant biologists, microbe experts, statisticians, and computational biologists..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

In this lesson and its associated activity, students conduct a simple test to determine how many drops of each of three liquids can be placed on a penny before spilling over. The three liquids are water, rubbing alcohol, and vegetable oil; because of their different surface tensions, more water can be piled on top of a penny than either of the other two liquids. However, this is not the main point of the activity. Instead, students are asked to come up with an explanation for their observations about the different amounts of liquids a penny can hold. In other words, they are asked to make hypotheses that explain their observations, and because middle school students are not likely to have prior knowledge of the property of surface tension, their hypotheses are not likely to include this idea. Then they are asked to come up with ways to test their hypotheses, although they do not need to actually test their hypotheses. The important points for students to realize are that 1) the tests they devise must fit their hypotheses, and 2) the hypotheses they come up with must be testable in order to be useful.

Most of the flavoring in gum is due to the sugar or other sweetener it contains. As gum is chewed, the sugar dissolves and is swallowed. After a piece of gum loses its flavor, it can be left to dry at room temperature and then the difference between its initial (unchewed) mass and its chewed mass can be used to calculate the percentage of sugar in the gum. This demonstration experiment is used to generate new questions about gums and their ingredients, and students can then design and execute new experiments based on their own questions.

In this 2-part inquiry-based lesson, students conduct a literature search to determine the characteristics of the atmospheres of different planets (Venus, Mercury, Mars and Earth). After collecting and analyzing data, student teams design and conduct a controlled physical experiment using a lab apparatus to learn about the interaction of becomes CO², air, and temperature. The resource includes student worksheets, a design proposal, and student questions. Connections to contemporary climate change are addressed. This lesson is the first of four in Topic 4, "How do Atmospheres Affect Planetary Temperatures?" within the resource, Earth Climate Course: What Determines a Planet's Climate?

How to do science: a guide to researching human physiology has been written for students of the life sciences who are actively engaged in the scientific process. A lot of support is available for students learning scientific facts, but we found that it was harder to find resources to support students to become scientists.

This ebook introduces you to what it means to be a scientist. You will learn about the scientific method and how to do many tasks of a scientist, your roles and responsibilities as a scientist as well as possible career paths, and how to use your skills as a science graduate to get a leg up in the job market.

This text is published by the La Trobe eBureau.

This course surveys the core perceptual and cognitive abilities of the human mind and asks how they are implemented in the brain. Key themes include the representations, development, and degree of functional specificity of these components of mind and brain. The course will take students straight to the cutting edge of the field, empowering them to understand and critically evaluate empirical articles in the current literature.

Despite the potential benefits of sequential designs, studies evaluating treatments or experimental manipulations in preclinical experimental biomedicine almost exclusively use classical block designs. Our aim with this article is to bring the existing methodology of group sequential designs to the attention of researchers in the preclinical field and to clearly illustrate its potential utility. Group sequential designs can offer higher efficiency than traditional methods and are increasingly used in clinical trials. Using simulation of data, we demonstrate that group sequential designs have the potential to improve the efficiency of experimental studies, even when sample sizes are very small, as is currently prevalent in preclinical experimental biomedicine. When simulating data with a large effect size of d = 1 and a sample size of n = 18 per group, sequential frequentist analysis consumes in the long run only around 80% of the planned number of experimental units. In larger trials (n = 36 per group), additional stopping rules for futility lead to the saving of resources of up to 30% compared to block designs. We argue that these savings should be invested to increase sample sizes and hence power, since the currently underpowered experiments in preclinical biomedicine are a major threat to the value and predictiveness in this research domain.