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.

" 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 "

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.

Introductory statistics course developed through the Ohio Department of Higher Education OER Innovation Grant. The course is part of the Ohio Transfer Module and is also named TMM010. For more information about credit transfer between Ohio colleges and universities please visit: www.ohiohighered.org/transfer.Team LeadKameswarrao Casukhela                     Ohio State University – LimaContent ContributorsEmily Dennett                                       Central Ohio Technical CollegeSara Rollo                                            North Central State CollegeNicholas Shay                                      Central Ohio Technical CollegeChan Siriphokha                                   Clark State Community CollegeLibrarianJoy Gao                                                Ohio Wesleyan UniversityReview TeamAlice Taylor                                           University of Rio GrandeJim Cottrill                                             Ohio Dominican University

In this module we will study experimental designs. We will learn about the principles of a good experimental design, the relative advantages and disadvantages of each method.Learning Objectives:Principles of experimental designs – control, randomization and replicationExperimental Vs. Sampling MethodsComparative Experiments – Completely Randomized Design, Randomized Block Design, Factorial DesignMatched Pair DesignClinical Trial and Double-Blind ExperimentsExperimental Ethics