& Data Analysis
Protein gel analysis
Keeping a lab notebook
Writing research papers
Dimensions & units
Using figures (graphs)
Examples of graphs
Principles of microscopy
Solutions & dilutions
Fractionation & centrifugation
Radioisotopes and detection
Writing and Analytical Resources
As reference materials, the pages presented here are generic in nature rather than course specific. They include universal truths and practices, and are used not only in this course but by other courses in the program and even by programs elsewhere.
All of the analytical resources were developed for the natural sciences and engineering laboratory program and are shared by multiple courses in several disciplines. These shared resources are written as portable document files (pdf) and are stored on a different server from the one supporting this course web site. When you follow a link to such a file it should appear in a new window.
Keeping a laboratory notebook
This section presents guidelines and examples for starting and keeping a laboratory notebook in the introductory laboratory course. Requirements are probably more rigid than what would be expected for a notebook in a typical academic research laboratory. On the other hand, they are definitely less rigid than requirements for recordkeeping in a research department in industry, or for any type of proprietary research for that matter.
The guidelines presented on these pages would apply to a typical manuscript to be submitted for publication in a scientific journal. The specifics do not necessarily apply to all journals, however the guidelines do introduce and reinforce the need to follow editorial requirements and adhere to general principles for effective writing. Each part of a journal article accomplishes a specific and unique purpose, allowing a person to read selectively. Such writing is good practice for specialized forms of written communication that will very likely be expected of the student some time in the future.
This section addresses very specific objectives. It introduces the importance of statistical methods in addressing the uncertainty contributed by experimental error. Probability values and hypothesis testing are introduced using only two types of statistical tests as examples : 'Student's' t test and the Chi-squared goodness of fit test.