Meetings:  Individual Appointments

Instructor: Jim Dooley - BSC 428; 8227; jdooley@muskingum.edu; 

Texts: See CVSC 437/Biol 420

• First we wanted to facilitate your introduction to scholarly literature.   The goal was to identify and develop a few specific testable hypotheses (in which data may be feasibly collected that will support or refute these hypotheses).

• Secondly, we worked towards the development of a formal research proposal that properly motivated a compelling  research question as well as outlined a  feasible procedural plan to collect your data.  We placed a great deal of emphasis on the elements of experimental design including the development of adequate sampling designs, anticipation of analytic methods, and estimation of project costs.

This semester in CVSC 438/Biol 421 your goals will be to:

• Complete data collection and analysis.
  

• Prepare and submit an abstract of your research to the Ohio Academy of Science for the spring meeting.  In order to allow ample time for review of your abstract among all authors (be sure to list any faculty from the Wilds that helped you as coauthors.  See my example document for details) your abstracts will be due in for my review on 1 October.
  

• Develop a highly polished draft of your thesis thorough the results section. 

Course Requirements for CVSC 438/Biol 421:

• Within the two weeks of the semester, each student will be responsible for establishing a weekly meeting time with their research advisor

• You will prepare a poster for the Science Division's Fall Research and Internship Poster Forum

• You will need to turn in updated and revised versions of your introduction and methods sections by the middle of the term.   
  

• Students should plan on preparing and submitting an abstract of their work to the Ohio Academy of Sciences in early November in order to participate in the annual meeting that occurs in April.

• At the end of the term you will turn in a draft of your thesis that includes introduction, methods, and results sections. The introduction and methods sections should be more or less a final version (that is very polished) with updated references to the new primary literature you have read.   The results section need not be a final version, but it should be close and definitely complete with figures, any tables and all major analyses complete. 

So what should you think about in developing your "Results" section?

Given  the aim of this course is to produce a high quality draft of your thesis through the results section we should be starting the semester with a fairly strong foundation of introduction and methods, we might start here with the question, "what is a results section and how do you develop one?"  To start with, we can say that the results is one of the five major sections of a scientific paper (introduction, methods, results, discussion, literature cited).   It's really very simple: the job of the results section is to present the important findings from the research effort.  

Almost as important as knowing what a results section is, is knowing what it is not ... this is not the part of the paper in which findings are interpreted (that is the job of the discussion).   In some ways then the challenge is simply to sort out what  findings most directly bear on the questions that  underpin the study, present those findings, and then move on.

Generally speaking your results section should be designed to present information emerging from analyses of the raw data you collected.   Almost always, raw data needs some form of analysis in order to extract whatever patterns or insights about causal relationships that might exist (even simple graphing means or sums constitutes forms of analysis).   The nature of your questions will suggest what sorts of analyses would best serve your purposes (note: we will be working further on how to make the question-analysis connection this term).

Once you finish data collection and entry into Excel, your next step will be to summarize your data.  To do this, you may want to calculate some descriptive statistics (very often means and standard errors).  So if you were looking at feeding rates of birds at feeders that were at two different distances from woods (near, far), you might want to compute means and standard errors of feeding rates you observed across replicated sites - each with feeders set up in the same fashion. You can use easily use Excel to accomplish this.  SPSS (the statistical package we discussed for sophisticated statistical analyses) can be used if you'll need  a great many or variety of descriptive statistics.  If you have collected demographic data from some population (e.g., small mammals or birds), you may need to use some kinds of estimation procedures (e.g., Program Mark or Mayfield Methods) in order to develop statistics such as population size, survival rates, reproductive success, movement rates etc.).

Once you have summarized your data and/or developed any derived estimates you may need, your next step will be to use Sigma Plot to generate graphs (software is available on the computer in room 428 next to Danny Ingold's office).  In particular, you should think about using bar or line graphs to show the relationship  between your dependent (response) and independent (predictor variables).  So, continuing with our example, if you were looking at feeding rates of birds at feeders that were at two different distances from woods, you might construct bar graphs with mean feeding rate on the "Y" axis and different bars for each distance class from the woods.   Graphing your data will give you an initial sense of what kind of patterns you might have.  In the case of experiments, graphing results can begin to guide your thinking about mechanisms that might be driving responses.  

After producing your initial graphs and reflecting a bit on what they suggest, it is time to conduct any inferential analyses that are appropriate.  Before firing off a bunch of SPSS tests, it is a good idea to once again revisit your project questions.  Doing so will help you frame out the details of your analyses (e.g., the type of test, nature of test options you may want to employ).  Please be sure to see your research advisor for input at this stage.

After your graphs and statistical analyses are done it is time to start writing your results section.   Again, in many cases designing this section to follow the sequence of your project questions can provide and relatively straight-forward means of writing.   Describe the patterns/responses you see by reference to your figures first and then follow up with references to statistical tests.  For example:

"Feeding rates for sparrows were highest near the woods (x = 236.6  ± 13.1 g/hr) relative to more distance feeders (x = 113.2  ± 24.2 g/hr).  Indeed, feeding rates were significantly higher at the near- relative to the far distant sites (F = 16.7, d.f. = 1, p < 0.03)."

 In some cases (particularly if your questions are a bit open ended) if can be hard to sort out exactly which findings need to be presented - work with your advisor in addressing this issue.  Your research advisor will be happy to provide you with examples of papers that model this sort of approach to developing a results section.   Often  reviewing other papers at this stage with an eye towards the style they use (as opposed to focusing on content which is what we typically do in reading journal papers) can provide some important tips or insights that can prove very helpful.

I
What information goes into the abstract you submit to the OAS and what sort of format should you follow?

An abstract is basically a short digest of a research project.   The abstract should:

• Precisely follow the format outlined by the OAS - I can provide you with a "how-to" document with examples - be sure to ask me for this. 
• Be sure to list any faculty from the Wilds that helped you as coauthors.
  
• Provide a short (1-2 sentence) overview that motivates the research
• Clearly identify the research objective or questions
• Identify the most important results that have emerged thus far
• Provide a short (again 1-2 sentence) interpretation of those results