Unit 1 Concept 0 • Biology Review – Scientific Method & Experimental Design

Scientific Method

• Definition: A step-by-step process used by scientists to investigate phenomena, gather evidence, and draw conclusions from experiments & observations.

• Purpose: Provides a logical, repeatable, and transparent framework for answering questions about the natural world.

• 6 Major Steps (in order)

  • Make an Observation

  • Ask a Question about the observation

  • Propose a Hypothesis (testable explanation / prediction)

  • Design an Experiment to test the hypothesis

  • Collect Data (measure, record, organize)

  • Draw a Conclusion based on data analysis

• Practical importance

  • Ensures findings are evidence-based rather than anecdotal

  • Allows other scientists to replicate work and verify results

  • Encourages iterative refinement—conclusions can feed back into new observations & questions

Hypothesis Basics

• Working definition: Testable predictions that can be examined by additional observations or experiments.

• Common (but optional) wording: “If … (IV) then … (DV) because … (rationale).”

  • “If” → manipulated variable = Independent Variable (IV)

  • “Then” → responding variable = Dependent Variable (DV)

  • “Because” → optional causal explanation providing biological logic

• Results can support or refute the hypothesis, but:

  • NEVER state “the hypothesis is correct.”

  • A supported hypothesis is still provisional; future evidence could refute it.

Null & Alternative Hypotheses

• Scientists always start with a null hypothesis as the formal statement to test.

• Null Hypothesis (H_0)

  • Claims no difference / no effect between two groups or treatments.

  • Serves as the baseline that statistical tests attempt to disprove, reject, or nullify.

  • Significance: By rejecting H_0, researchers gain confidence that observed patterns are not due to chance alone.

  • Example: H_0 – “There will be no difference in headache relief between individuals who take Tylenol and those who do not.”

• Alternative Hypotheses (H1, H2, H_3, \dots)

  • State the specific outcomes the researcher expects once H_0 is rejected.

  • Multiple alternatives can be listed (labeled H1, H2, H_3, etc.) if the experiment can yield several possible effects.

  • Example alternatives for the Tylenol study:

  • H_1 – “Tylenol will allow for headache relief when consumed.”

  • H_2 – “Tylenol will worsen symptoms when consumed.”

Experimental Design Essentials

• Groups & Replication

  • At least 3 trials per group to obtain reliable averages and support statistical analysis.

  • Two core group types:

  • Control Group – Benchmark for comparison; validates that results arise from IV and not external variables.

  • Experimental Group – Receives the IV treatment to assess its impact on the DV.

• Control Sub-types

  • Negative Control

  • Group not exposed to the IV OR exposed to a treatment known to have no effect.

  • Ensures that no effect occurs when none is expected, helps detect contamination or hidden variables.

  • Positive Control

  • Group exposed to a treatment known to elicit a specific, expected effect.

  • Confirms that the experimental setup is capable of detecting an effect at all (i.e., the assay works).

• Example – Caffeine & Heart Rate (Negative Control)

  • Research Question: Does caffeine affect heart rate?

  • Negative control receives water (known to have no effect).

  • If water group still shows heart-rate change, researcher must suspect another variable or contamination.

• Example – New Antibiotic (Positive Control)

  • Research Question: Is a new antibiotic effective against a bacterial strain?

  • Positive control receives a well-established antibiotic known to kill the bacteria.

  • If new antibiotic groups fail yet the positive control works, the new compound is likely ineffective (setup still valid).

Variables in an Experiment

• Independent Variable (IV)

  • The one factor purposely changed between groups.

  • Graphed on the x-axis.

• Dependent Variable (DV)

  • The factor measured / observed; expected to change in response to the IV.

  • Graphed on the y-axis.

• Constants / Controlled Variables

  • All other factors kept consistent across groups so that only the IV influences the DV.

  • Reduce confounding influences and increase internal validity.

Practical & Philosophical Implications

• Emphasizing H_0 demonstrates scientific objectivity—researchers attempt to disprove their own default assumption.

• Proper controls (positive & negative) provide ethical responsibility: ensure no false claims of effectiveness (e.g., pharmaceuticals).

• Adequate replication (\ge 3 trials) respects statistical power and reproducibility, defending conclusions from random chance.

Quick Study Checklist

• [ ] Can you list the 6 steps of the scientific method in order?

• [ ] Are you comfortable crafting H0 and at least one H1 for any given research problem?

• [ ] Can you distinguish between negative and positive controls and give examples?

• [ ] Do you know where IV, DV, and constants appear on a graph?

• [ ] Can you explain why “support” ≠ “prove” in scientific language?