Scientific Method and Experimental Design Practice Flashcards
Experimental Manipulation and Variables
Causal studies require experimental manipulation to determine the relationship between specific factors and observed responses.
Experiments must be organized into distinct groups to establish a point of comparison:
Control Group: This functions as the baseline group. No manipulation is performed, and organisms are observed under normal conditions to establish a baseline response.
Experimental Treatment Group: One specific factor is manipulated in this group to observe its effect on the response.
Variables in a study are categorized as follows:
Independent Variable: The factor that is manipulated by the researcher (e.g., the amount of fertilizer applied to plants).
Dependent Variable: The factor being measured in response to the manipulation (e.g., plant growth height or the volume of tomato production).
Standardization of Variables: To ensure causality, every factor other than the independent variable must be kept constant between the control and experimental groups. These standardized variables include light, water, and temperature.
Advanced Experimental Controls: Placebos and Sham Treatments
In complex experimental designs, specialized controls are used to account for psychological or physiological biases.
Placebo Control: Commonly used in human drug studies. Participants are given an inactive substance (e.g., a sugar pill) while being told they are receiving treatment.
A placebo accounts for the improvement in a patient's condition simply because they believe they are being treated (the placebo effect).
In a drug study, both groups undergo the same process (seeing a doctor, taking a pill), but the chemical activity of the pill differs.
Sham Control: Used primarily in animal studies to control for the physical effects of a procedure rather than the actual manipulation.
Intestine Removal Example: If testing how removing part of a mouse's intestine affects digestion, the experimental group has the surgery performed.
The sham group is anesthetized, cut open, and the intestine is located and touched with a scalpel without being cut or removed. The mouse is then sewn back up and allowed to recover.
This controls for confounding factors such as anesthesia, surgical pain, recovery stress, and pain medication, ensuring that differences in digestion are solely due to the missing intestine.
The Role of Variation and Replication
Replication is critical because individual organisms within a population exhibit significant variation in behavior, body size, physiology, and metabolic rates.
Experimental groups must be representative of the larger population to draw accurate conclusions about that population.
Spatial Bias: When setting up replicates, they should not be grouped by treatment (e.g., all experimental groups in one area). Factors like air conditioning vents or light from windows can create unintended gradients in temperature or brightness. Mixing treatment and control replicates throughout a space prevents these external factors from biasing one group over another.
Experimental Design Strategies: Randomization and Blinding
Assigning individuals to control or experimental groups must be done randomly to ensure the experiment replicates the variation found in nature.
Blinding: This technique prevents conscious or unconscious researcher bias when collecting data.
Single-Blind Study: The experimenter does not know which treatment a specific subject has received while they are measuring results (e.g., measuring Plant ID #123 without knowing if it received fertilizer).
Double-Blind Study: Neither the subject receiving the treatment nor the experimenter administering it and measuring the outcome knows which treatment is being used. A third party manages the group assignments.
Determining Experimental Units and Scale
The definition of a replicate can vary depending on the field of study.
Fish Tank Dilemma: In a study with 15 control fish and 15 experimental fish, placing all control fish in one tank and all experimental fish in another is poor design. A single spurious event (e.g., a cockroach carrying pesticide landing in one tank) could kill all fish in that group, leading to the false conclusion that the treatment was lethal.
Trade-offs in Scale: Proper replication may involve many separate tanks (e.g., 15 per group) or "blocking," a statistical method to account for individuals sharing the same environment (e.g., three tanks with five fish each).
Scale of Study:
Ecological Studies: Replicates can be large-scale units like forest patches. A study on forest fragmentation used patches ranging from 1 acre to over 100 acres, with only three replicates per treatment due to spatial constraints.
Lab Studies: Research with crickets or spiders typically utilizes 15 to 20 individual replicates per treatment group.
Basic versus Applied Science
Basic Science: Focused on the generation of knowledge for its own sake.
Example: Researching sexual cannibalism in spiders to learn why females eat males and the nutritional effects on offspring.
This research does not immediately aim to cure diseases or solve global crises but builds the foundation of human knowledge.
Applied Science: Focused on solving specific, practical problems.
Example: Studying quail populations in Western Oklahoma to determine optimal insect diets for conservation management.
The Relationship: Basic science provides the essential understanding of how natural systems function, which is required before applied science can solve problems like cancer or climate change.
Data Interpretation and Figure Analysis
Data is typically collected in spreadsheets containing hundreds of values; figures are used to summarize these values and identify visual patterns.
Graph Components:
X-axis (Horizontal): Contains the Independent Variable or treatment group.
Y-axis (Vertical): Contains the Dependent Variable or measured response.
Correlational Plots: Individual replicates are plotted as points to show relationships (e.g., the amount of nitrogen in soil versus plant growth height).
Statistics: Independent calculations used to objectively determine if a pattern is a "significant" effect rather than a result of random chance.
P-value (): A value less than (p < 0.05) is generally considered statistically significant.
The Null Hypothesis: Every experiment must account for the possibility that the independent variable has no effect. Data must be able to falsify the hypothesis.
Case Study: Morphology and Behavior in Ants
Turtle Ants (Cephalotes): Also known as acrobat ants due to their heart-shaped abdomens.
They have specialized soldiers with round heads used to physically plug the holes of their nests in tree stems.
They are notable for being the only North American ants observed to successfully outfight red imported fire ants on trees.
Giant Ants (Dinochonera): Found at Iguodu Falls on the border of Argentina and Brazil.
Individual ants are the size of a human thumb and possess potent stingers.
The nesting colonies can reach depths of 3 to 4 feet underground.
Ant Walking Speed Experiment:
Hypothesis: Does ant type (independent variable) affect walking speed (dependent variable)?
Controlled Variables: Substrate (e.g., same paper vs. gravel), age of the ants, and species.
Statistical Representation: Asterisks and bars are used in figures to indicate which ant types possess a statistically significant difference in speed compared to others.
Case Study: Botox Treatment for Migraine Headaches
Experiments tested Botox as a treatment for migraines using two groups: a placebo group (injected with saline) and a Botox treatment group.
Study Design: The initial phase was a double-blind phase, followed by an open-label phase where participants were told which treatment they were receiving.
Results:
Placebo Effect: The placebo group reported a reduction of 6 to 7 headache days per month. Simply visiting a doctor and receiving an injection caused people to feel better.
Botox Effect: The experimental group reported a reduction of 8 to 10 headache days per month.
Conclusion: While Botox is effective (p < 0.05), the actual drug effect is smaller than the total observed improvement because much of that improvement is due to the placebo effect. This highlights the necessity of proper control groups.
Science versus Pseudoscience
Science:
Testable and falsifiable.
Based on empirical, quantitative data and replicated experiments.
Welcomes criticism through rigorous processes like peer review, where independent scientists critique findings before publication.
Pseudoscience:
Not testable or not tested.
Based on anecdotal evidence, beliefs, or myths.
Shuns criticism.
Example (Bigfoot): Bigfoot research is pseudoscience because it is not falsifiable. When a search yields no physical evidence, the conclusion is "Bigfoot is still out there; we just didn't see him," rather than "Bigfoot does not exist."
Example (Water Divining): Scientific testing has shown that people using rods to find underground water pipes perform no better than random chance when the water flow is changed blindly.