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.

Una guida rapida alla sperimentazione con soggetti e all'analisi statistica dei dati, nel contesto del design di oggetti interattivi.

In the first part of the activity, each student chews a piece of gum until it loses its flavor, 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 of four to design and conduct new experiments based on questions of their own choosing. These questions arise naturally from observations that occur during the first experiment, and from students' own experiences with and knowledge of the many varieties of chewing and bubble gums available.

This team taught, multidisciplinary course covers the fundamentals of magnetic resonance imaging relevant to the conduct and interpretation of human brain mapping studies. The challenges inherent in advancing our knowledge about brain function using fMRI are presented first to put the work in context. The course then provides 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, building and applying statistical models for fMRI data. Human subjects issues including informed consent, institutional review board requirements and safety in the high field environment are presented.

" 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 "

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.

Students are asked to develop a procedure for the determination of the amount of ascorbic acid in fresh and boiled cabbage tissue. In order to accurately determine the ascorbic acid content, students must take into consideration the following: a representative sample, aliquots, the boiling procedure, the presence of the enzyme ascorbic acid oxidase, and the release of ascorbate into the boiling water.

This lesson is the second of two that explore cellular respiration and population growth in yeasts. In the first lesson, students set up a simple way to indirectly observe and quantify the amount of respiration occurring in yeast-molasses cultures. Based on questions that arose during the first lesson and its associated activity, in this lesson students work in small groups to design experiments that will determine how environmental factors affect yeast population growth.

This course is a project-based introduction to manipulating and characterizing cells and biological molecules using microfabricated tools. It is designed for first year undergraduate students. In the first half of the term, students perform laboratory exercises designed to introduce (1) the design, manufacture, and use of microfluidic channels, (2) techniques for sorting and manipulating cells and biomolecules, and (3) making quantitative measurements using optical detection and fluorescent labeling In the second half of the term, students work in small groups to design and test a microfluidic device to solve a real-world problem of their choosing. Includes exercises in written and oral communication and team building.

This course will introduce the student to research methodologies frequently used in the social sciences, and especially those used in the field of psychology. This course covers the basics of conducting research, touching upon statistics and their importance (although it does not require a comprehensive knowledge of the subject). The course will conclude with a section on experimental design. By the end of this course, the student should understand why research methodology is important in scientific research, be comfortable reading procedural and methodological sections of journal articles, and understand how to employ different research methods. (Psychology 202A)

This course intends to acquaint the student with a variety of different research techniques. In this lab course, the student will put research and experimental design concepts into practice while conducting laboratory experiments. In addition to review of concepts developed in the Research Methods lecture course, this lab will also broach a number of practical matters, including the standard organizational format for research project documentation. (Psychology 202B)

Short Description: This is an inquiry investigation, geared toward student use of outdoor schoolyard sites. Its focus is to have students applying what they've learned about the scientific method and experimental design, gathering quantitative evidence to support hypotheses.

The first laboratory course biology majors take should challenge their expectation that biology is the mere memorization of knowledge. Rather, it should introduce them through experience to the scope and limitations of scientific investigation. Following a brief introduction to epistemology and the nature and goals of science, this course provides students with a developing understanding of scientific thinking, methodology, and experimental design. During the final unit of the course students devise and conduct a test of a hypothesis they have independently generated, conduct appropriate statistical analysis, and write a report of the project.

6.780 covers statistical modeling and the control of semiconductor fabrication processes and plants. Topics include design of experiments, response surface modeling, and process optimization; defect and parametric yield modeling; process/device/circuit yield optimization; monitoring, diagnosis, and feedback control of equipment and processes; analysis and scheduling of semiconductor manufacturing operations.

Introduces students to basic properties of structural materials and behavior of simple structural elements and systems through a series of experiments. Students learn experimental technique, data collection, reduction and analysis, and presentation of results.

Descriptive and inferential statistics for the behavioral and neurological sciences are considered. Techniques such as t-tests, factorial analysis of (co)variance, correlation, multiple regression, and nonparametric tests are introduced. Subject provides an introductory overview of some advanced methods such as path analysis, factor analysis, discriminant analysis, and analysis of functional MRI data. Basic issues of research design and methodology intimately associated with data analysis are discussed.

This course introduces statistical tools and techniques that are routinely used by modern statisticians for a wide variety of applications. Upon successful completion of this course, the student will be able to: apply statistical hypothesis testing for one population; conduct statistical hypothesis testing and estimation for two populations; apply multiple regression analysis to analyze a multivariate problem; analyze the outputs for a multiple regression model and interpret the regression results; conduct test hypotheses about the significance of a multiple regression model and test the significance of the independent variables in the model; select appropriate multiple regression models using automatic model selection, forward selection, backward elimination, and stepwise selection; recognize and address issues when using multiple regression analysis; identify situations when nonparametric tests are appropriate; conduct nonparametric tests; explain the principles underlying General Linear Model, Multilevel Modeling, Data Mining, Machine Learning, Bayesian Belief Networks, Neural Network, and Support Vector Machine. This free course may be completed online at any time. (Mathematics 251)

This course introduces the basic concepts and methods of statistics with applications in the experimental biological sciences. Demonstrates methods of exploring, organizing, and presenting data, and introduces the fundamentals of probability. Presents the foundations of statistical inference, including the concepts of parameters and estimates and the use of the likelihood function, confidence intervals, and hypothesis tests. Topics include experimental design, linear regression, the analysis of two-way tables, sample size and power calculations, and a selection of the following: permutation tests, the bootstrap, survival analysis, longitudinal data analysis, nonlinear regression, and logistic regression. Introduces and employs the freely-available statistical software, R, to explore and analyze data.