Scientific Literacy & Scientific Process

Science relies on precise units; fluency in converting them is essential for reading papers, problem-sets, and lab work.
Common base units
- Length: centimeter, meter, kilometer, inch, foot, mile
- Mass: gram, kilogram, pound
- Time: second, minute, hour
Linear vs. square vs. cubic units
- Linear: simply the one-dimensional length.
- Square: area; require multiplying the linear unit by itself.
  • Example cube illustration: 4 small cubes per side → $4 \times 4 = 16$ little squares on one face (not 4).
- Cubic: volume; multiply the linear unit three times.
  • In the cube illustration: $4 \times 4 \times 4 = 64$ little cubes form one big cube.
Large–scale metric example
- 1 km = 1 000 m.
- Area of a square $1\,\text{km} \times 1\,\text{km}$ → $1\,000\,\text{m} \times 1\,000\,\text{m} = 1\,000\,000\,\text{m}^2$ (one million square meters).
- Volume of a cube $1\,\text{km}^3$ → $1\,000 \times 1\,000 \times 1\,000 = 1\,000\,000\,000\,\text{m}^3$ (one billion cubic meters).
Practice problems (posed in video)
1. How many meters in 5 km? $5 \times 1\,000 = 5\,000\,\text{m}$
2. How many m² in 5 km²? $5 \times (1\,000)^2 = 5\times1\,000\,000 = 5\,000\,000\,\text{m}^2$
3. How many m³ in 5 km³? $5 \times (1\,000)^3 = 5\times1\,000\,000\,000 = 5\,000\,000\,000\,\text{m}^3$

Long-term CO₂ record (Mauna Loa "Keeling Curve")
• Up-down seasonal wiggles: photosynthesis (summer) vs. respiration (winter) in N. Hemisphere.
• Overall upward trend: human fossil-fuel use & deforestation.
• Demonstrates value of decades-long funding & consistent methods.
Microscopy example: advanced equipment extends senses; techniques often invented just to enable observation.
Mars Rover: robotics allow observation on inaccessible planets.
Diverse research teams: investigators’ identities/backgrounds shape what questions seem important → diversity broadens science.
Scatter-plot (salinity vs. nitrogen) illustrates “pattern observation” rather than a lone data point; suggests freshwater delivers nitrogen, ocean dilutes it.
Spatial patterns & GIS mapping: powerful for pollution, species distributions; courses available in Environmental Science dept.

Specific & concrete, lends itself to a clear yes/no or quantitative answer.
Typically addresses:
• Causal relationships (Does X cause Y?)
• Patterns (How does Y vary with X?)
• Group differences (Is mean of group A ≠ group B?)
Wording often includes is / will / does. Avoid should / ought / good / bad (moral or philosophical language).
Must be answerable with observable/measurable data.
Ethics & values guide which questions matter but are not themselves answered by science.

Prediction/statement answering the scientific question, grounded in prior knowledge, logic, or observation.
Always at least two plausible hypotheses; potentially infinite.
Must be testable (potentially falsifiable).
Being wrong is okay—directs learning.
Framing highlights what variables the scientist thinks matter (e.g., tree height vs. wood properties vs. location for lightning strikes).

Possible outcomes:
• Supports hypothesis – makes it more plausible.
• Refutes hypothesis – renders it unlikely.
• Mixed/ambivalent – partial support; may require more nuanced study.
• Reveals study design issues – data suggest problem with method rather than hypothesis.
Strength continuum
• No evidence → weak → stronger → strongly supported → Theory (e.g., evolution).
• Absolute proof unattainable; science is iterative.

Observational Studies
• Measure variables in natural context; no manipulation.
• Often field-based; suitable for complex systems impossible to replicate (ocean circulation, elephant lifespan).
• Show correlation, not definitive causation.
Experimental Studies
• Manipulate a single variable; include control vs. experimental groups.
• Typically laboratory-based.
• Can establish causation but may oversimplify real-world complexity.

Observation: Suspect ran from scene and was covered in blood.
Scientific mindset: Generate alternate hypotheses (e.g., suspect discovered victim already bleeding and panicked; suspect tried to help and became bloody; actual killer fled earlier, etc.).
Purpose: Guard against single-cause bias; design studies (or investigations) that rule out alternatives.

Funding long-term monitoring (e.g., CO₂) is crucial for detecting slow trends; public policy must value sustained science.
Diversity in science enriches question framing and societal relevance.
Scientific results inform—but do not dictate—moral or policy decisions; stakeholders must integrate data with values.

Unit conversion skills appear in problem sets, literature (methods sections), and lab protocols.
GIS & spatial analysis skills applicable to environmental policy, conservation planning, urban design.
Understanding difference between correlation and causation essential for interpreting news articles, medical claims, climate reports.
Familiarity with hypothesis testing prepares students for designing capstone projects, internships, or independent research.

$4 \times 4 = 16\,\text{(squares)}$
$4 \times 4 \times 4 = 64\,\text{(cubes)}$
$1\,000\,\text{m} \times 1\,000\,\text{m} = 1\,000\,000\,\text{m}^2$
$1\,000^3 = 1\,000\,000\,000\,\text{m}^3$
Practice solutions: $5\,000\,\text{m};\ 5\,000\,000\,\text{m}^2;\ 5\,000\,000\,000\,\text{m}^3$

Complete & submit Canvas assignment (math conversions, best scientific question, write a hypothesis, alternate murder-scene explanations).
Optional: Watch supplemental videos + assignment on personal experience of nature.
Next lecture next week—have a great weekend!