Recordkeeping, Writing,
& Data Analysis


Microscope studies

Flagella experiment
Laboratory math
Blood fractionation
Gel electrophoresis
Protein gel analysis
Concepts/ theory
Keeping a lab notebook
Writing research papers
Dimensions & units
Using figures (graphs)
Examples of graphs
Experimental error
Representing error
Applying statistics
Principles of microscopy

Solutions & dilutions
Protein assays
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.

Analytical resources

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.

  • Dimensions and units [pdf] [html] Examples of dimensions, units, and dimensionless quantities; conventional choices for units; using prefixes; dimensional consistency; units conversion
  • Fundamentals of graphing [pdf] [html] overview; purpose, data, and variables; anatomy of a graph; scales, axes, and proportions; symbols, error bars, and fit lines; labels, legends, and captions; computer graphics
  • "Graphical errors"[pdf] [html] To plot or not to plot; a set of common mistakes; misleading scales; computer fits; guiding experimentation; transformation of variables
  • Example: plotting data with a computer program [pdf] [html] Program default; about line graphs and curve fitting; add essentials, remove non-essentials; proportion and orientation
  • Error analysis and significant figures [pdf] [html] Significant figures; absolute and relative errors; systematic errors; random errors; estimating random errors; propagation of errors
  • Error representation and curvefitting [pdf] [html] When to report random error; representing random error (assumptions, errors to use, reporting data in text or tables, representation with error bars); curvefitting (trendlines, true curvefiting)

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.

Research papers

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.

Statistical methods

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.

Copyright and Intended Use
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Created by David R. Caprette (caprette@rice.edu), Rice University Dates