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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?