Data-Driven Exercises For Chemistry

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Empirical data is at the heart of all scientific knowledge.  The acquisition of new knowledge is achieved through the scientific method, which is a cyclic process of analyzing data associated with physical phenomenon in order to determine whether the data conforms to a proposed model.  Models that are continually successful, and that can be used to rationalize a wide range of empirical evidence are ultimately promoted to the rank of theory.  Models that fail must be modified and tested again.
The ability to analyze data within the context of a model is a vital skill for a scientist.  Chemistry makes heavy use of mathematical models.  Consequently, the learning of chemistry is greatly enhanced by activities where one is presented with real-world data, and is guided to analyze the data according to a quantitative model.  These activities are even more rewarding when they introduce the student to new numerical methods, involve consideration of errors, and lead one to ultimately contemplate the validity of the model.
This web site contains a library of ‘data-driven’ chemistry exercises.  Assignments are arranged by topical area and include (1) a description of the goals, prerequisites and resources that will be needed to complete the assignment, (2) a brief theoretical description of the phenomena of interest and an explanation (or illustration) of the experiment that generated the experimental data, (3) the raw data, and (4) a suggested protocol of data analysis and questions that should be addressed.

Instructors and students are welcome to download exercises for personal and classroom use. Commercial use of any copywrited materials is not permitted without the permission of the copywrite holder.

Suggestions for improving this web site are welcome.  You are also encouraged to submit your own data-driven exercise to this web archive. All inquiries should be directed to the curator: Tandy Grubbs, Department of Chemistry, Unit 8271, Stetson University, DeLand, FL 32720.