Study Notes: Experimental Design, Model Organisms, and Course Logistics

Control groups and Experimental Groups

  • Control group: no treatment (baseline for comparison).
  • Experimental groups: receive the treatment; can have multiple groups with different treatment levels.
    • Example: caffeine study with three experimental groups: small amount, medium amount, large amount of caffeine.
    • All three experimental groups are considered experimental because they receive the treatment (caffeine).

Independent Variable and Dependent Variable

  • Independent Variable (IV): the treatment or condition you deliberately change/manipulate.
    • Examples from the transcript: amount of caffeine, temperature, amount of light, type of food.
    • The IV is what you’re altering to see its effect on the outcome.
  • Dependent Variable (DV): the outcome you measure after applying the treatment.
    • Examples from the transcript: mortality (alive vs dead), number of babies born, growth or thriving.
  • Relationship: IV (treatment) -> DV (outcome).

Standardized Variables (Controlled Variables)

  • Standardized variables are everything kept the same across groups to isolate the effect of the IV.
  • Aim: have one clear IV and one clear DV.
  • If you change multiple factors (lighting, food, temperature) you can’t tell which factor affected the DV.
  • Example from the transcript (survey):
    • Keep time of day the same, keep survey identical, and only vary the treatment (e.g., passing out candy).
  • Outcome: ensure only the treatment differs between groups.

Sample Size

  • Sample size = number of participants (units) in the study.
  • Transcript example: a class of 24 people; if they are the experimental group and receive food, the sample size is 24 (n = 24).

Hypothesis, Experiment, and Data Analysis

  • After running experiments, analyze the data.
  • You may form a new hypothesis based on results.
  • Example from the transcript:
    • Hypothesis: if I give candy to students, they will finish the survey more quickly.
    • Result: data showed the opposite (candy led to slower completion because students eat and socialize).
    • Conclusion: this is still valuable; science accepts that hypotheses can be false and you learn from the outcome.
  • Process insight: when data contradict a hypothesis, you can develop a new model or hypothesis and investigate why it happened.
  • Personal anecdote: a master’s project example where data contradicted an upcoming publication, leading to a new model based on the data.

Model Organisms

  • Definition: small organisms used to run tests in the lab.
  • Common examples mentioned: copepods, rats, mice, worms (e.g., C. elegans), and Drosophila (fruit flies).
  • Reasons they’re useful:
    • Small size and space efficiency (e.g., copepods in a small tank).
    • Short lifespan and rapid reproduction (e.g., generations every ~4 weeks, allowing several generations in a short period).
    • Grow well in the lab.
    • Share some genetic similarity with humans; closer to mammals often implies more similarity, but Drosophila has many human-like genes.
  • Ethical and practical considerations:
    • Mice and rats are common model organisms for preliminary testing before humans.
    • Model organisms reduce ethical concerns and logistical barriers compared to testing first in humans.
  • Real-world practice mentioned:
    • UNC labs and doctors (e.g., cancer treatment research in mice; fatty liver treatment) use mice as a model.
    • Opportunities to get involved in research can enhance resumes and understanding; instructors encourage contacting them for guidance.

Practical implications and takeaway

  • Model organisms are chosen for their practicality and relevance to human biology while balancing ethical constraints.
  • Early exploration in model organisms informs potential effects in humans before any human testing.
  • The scientific method embraces learning from results that contradict initial ideas and evolving models accordingly.

Course logistics and upcoming deadlines

  • Homework two is due Monday by 11:59 PM. The syllabus states no late homework is accepted.
  • Last week some students submitted late and received zeros due to the late policy; one missed homework does not drastically affect overall grade, but missing all six homeworks would be problematic.
  • A reminder will be sent about this weekend.
  • Next week: final research question due, similar to the preliminary question with required tweaks and edits based on feedback.
  • Remember to do the reading before coming to class.
  • For today, pull up your lab exercises and proceed with the material.