Check-list for improving lab reports
- Logic: start the paragraph with the main idea, then describe it and prove. The logic is often incomplete, i.e., you don't finish the chain of your statements. For example, "Defoliation was estimated from egg mass density, but weather and other factors may play an important role in gypsy moth population dynamics". It is necessary to add: "Therefore, weather may also affect defoliation".
- Abstracts: put your major results rather than describing what you did.
- References to figures and tables in the text are often missing
- Include all equations that you use in the paper. Number equations and make references to then throughout the text. Use Microsoft Equation Editor to make equations! All variables in equations should be explained.
- Delete non-informative sentences, e.g., "Means and variances are shown in Table 1". Instead of it write: "Mean egg mass densities varied from ??? to ??? among the blocks (Table 1)"
- Abbreviations (CD) should be explained at first use.
- Give definitions to the terms that may be unknown to some readers (e.g., CD, mean crowding).
- Second-order headers are needed in "Methods" and "Results".
- Methods should be absolutely clear, so that a student who did not make this lab can repeat it. For example, the method of moments was not mentioned in some reports.
- Check the titles for graphs and tables. They should be complete and self-describing. The rule is that the reader should be able to understand the graph or table without reading the text.
- Some of you did not use any additional information from papers and from the net. Consequently, the discussion was very poor.
- Clearly distinguish between a fact and its interpretation. This can be done by correct placement of references to tables and figures.
- Don't use extra digits in numbers! Use function ROUND(number, no. of decimal digits) to round your numbers.
- Always give equations for all linear regressions you plot, and for other straight lines, e.g., in the sequential sampling plan #2.
- Most of you did not notice that gypsy moth egg masses were not aggregated at low densities. Use diagonal lines in mean crowding regression and in Taylor's power law regression to prove this. In Taylor's regression, the diagonal line correspond to MEAN = VARIANCE which is characteristic to the poisson distribution (CD = 1).
- Nobody discussed the gradient of gypsy moth density (it was increasing from west to east). Can you explain this gradient knowing that the area was on the leading edge of the expanding population?