Chapter 1 Introduction

Welcome to experimental design. There are two sets of three exercises provided to explore principles for better experiments. This is a simple book to support the practical, at-home learning associated with experimental design. The text ‘Experimental Design for the Life Sciences’ underpins the design principles (Ruxton and Colgrave. 2018).

Life is an experiment. Individually and collectively. We experiment everyday. This is an opportunity to formalize some of those processes and make the learning from experimental design thinking a craft you can apply to all challenges. There are two primary modules to support this process.

  1. Field experiments comprises three outdoor experiments to explore sampling heterogeneous, complex processes in natural systems. The purpose is to provide choice. You need to try each, briefly, as a pilot experiment only. Then, select one to pursue in depth and write up as a research article.

  2. The data experiments describe the opportunity to use design thinking to structure existing data that others have already collected. The same principles for better experiments still apply in how you reuse the data. There are also three examples provided. Select only one and write up as a note.

Both report formats supported by FACETS. It is the first and only open access science journal in Canada.

Workflow for pilot and field experiment

  1. Do all three field experiments in brief, pilot only, try each for a few hours each.
  2. Then, Select one of the first three field experiments to publish data with meta-data.
  3. Publish your data with meta-data to an open and public data repository such as figshare.
  4. Share the link with all the files with the teaching assistment via the course platform.
  5. Select one of the three field experiments to do a deeper dive, i.e. fuller experiment wherein you structure observation by a key variable in the environment.
  6. Design experiment, collect data for the deeper dive.
  7. Consider combining data from other students that examined the same system.
  8. Publish data with meta-data to figshare and submit to teaching assistant via
  9. Write up the field experiment you completed for the deeper dive as a research article for the Canadian open science journal Facets.
  10. Submit paper to teaching assistant via

Field experiments gear

field lab gear purpose
birdwatching lawn chair or balcony a good spot to sit and observe birds
birdwatching field guide or smartphone support identification
birdwatching binoculars, scope, smartphone facilitate spotting and take pics (not critical)
bioblitz practical shoes good for thoroughly surveying your identified space
bioblitz smartphone iNaturalist app (not required but useful)
bioblitz smartphone take pics of animals
bioblitz net sweep and capture then release insects (not critical)
surveys practical shoes walking around your 50m outdoor space
surveys measuring device for transect tape, rope, phone with digital ruler, anything you can lay or run out for 50m
surveys linear object for quadrat bamboo, stick, pvc pipe, broom handle cut up, anything that is 0.5m long, preferably make a square

Workflow for the data-design lab report

  1. Explore each dataset.
  2. Plan a variable to structure your design and analysis.
  3. Reuse the data to explore your hypothesis and test your predictions.
  4. Write a short research ‘note’ format paper suitable for publication in Facets journal.
  5. Submit paper to teaching assistant via

Data-design experiments gear

data lab gear purpose
all three data labs access to computer or tablet download dataset, explore data
all three data labs R, Python, or any free stats app plot data and do stats
all three data labs internet access to download data and submit note to teaching assistant
all three data labs Google Scholar or Web of Science check literature on key topics
magic a pack of cards consider getting a pack to think over process (not critical)
diversity look for photographs online explore how the data were collected visually
human check out fitbits and trackers check out watches, fitbit, trackers and explore limitations (not critical)

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