Nature of Science - Comprehensive Study Notes

Course logistics and setup

  • The instructor discusses submitting videos for the course and YouTube usage
    • You cannot create a private YouTube account; use a normal YouTube account
    • Mark videos as private, public, or unlisted
    • Record a video, save it to OneDrive or MSU cloud, and share the link for the meeting
    • Instructions for sharing links are on Blackboard under syllabus/course documents (document that says "how did you find the file?" and then "share with me") so the instructor receives only the link, not the actual file
    • Video formats: mp4 or .mov; not QuickTime (or at least ensure compatibility)
  • Submission process and timing
    • Videos should be uploaded to Blackboard with a timestamp; this serves as plan B if there are upload issues
    • You must watch two videos and submit two video summaries via OneDrive link or YouTube link before Saturday night
    • Check the syllabus for specific recording instructions; failure to follow instructions may cost points
  • Course schedule and class logistics
    • First/second quizzes: a) reading-based multiple choice, b) PowerPoint-based multiple choice
    • Quiz number one on September 3; a sampler of questions will appear in the MC section of the quiz; short answers based on activities
    • A portion of class time is dedicated to PowerPoint material and activities
  • General encouragement and issue handling
    • If there is a technical issue, the student will not lose points
    • Students are reminded that sometimes people record videos before the deadline and forget to submit; timestamps matter
  • Administrative check-ins (tables)
    • Several “Table” prompts ask for questions, comments, or concerns about syllabus, testing, assessments and due dates; there is a structured rotation for student questions

What is science? Principal elements of the nature of science

  • Science aims to describe and explain the natural world
  • Science has multiple viewpoints/perspectives:
    • Facts and concepts (typical textbook content): e.g., water is made of two elements, H_2O
    • Process of science: systematic, structured methods to obtain data
    • Developing hypotheses
    • Observing phenomena
    • Inferring and reaching conclusions
    • Using data to predict and identify patterns
    • Distinguishing variables: identifying the measuring variable, the manipulated variable, controls, and how to keep an experiment fair
    • Science as a worldview: thinking scientifically shapes how we interpret everyday life
  • Non-scientific worldviews exist (and are valid as beliefs):
    • Superstitions (e.g., ladders and black cats as omens)
    • Religious or spiritual beliefs (
    • Conspiracy thinking (e.g., extraterrestrials, global warming as a hoax, AIDS as a lab weapon)
    • These are not scientific because they rely on faith or untestable claims
  • Science is based on observations, experiments, and evidence
    • Some fields rely more heavily on observations (e.g., Astronomy) when experiments are not feasible; others combine observations and experiments (Biology, Chemistry)
    • Science knowledge is reliable but tentative: new evidence can modify what is accepted (e.g., Pluto’s planetary status)
  • Historical/phenomenal examples illustrating tentative/revisable knowledge
    • Pluto reclassification from planet to dwarf planet due to orbital characteristics and mass; needs a “clean” orbit
    • Early beliefs about butter vs margarine shifting over time with new evidence
    • COVID-19: masking became standard as understanding of transmission evolved
    • X-rays: dangers discovered later; safety protocols developed (lead shielding, restricted exposure)
    • Paris green and other historical chemicals/pigments later recognized as hazardous; toothpaste radium example shows how new data changes practices
  • Imagination and data limitations
    • Scientists use imagination to generate possible relationships; data are often incomplete
    • Not all beliefs or hypotheses can be tested; beliefs outside testable science fall outside science’s domain
  • Bias and objectivity
    • Scientists strive to avoid bias; conclusions should rely on data and evidence, not ideology
    • Science is not authoritarian; it’s bottom-up (individual researchers publish; consensus emerges)
  • Scientific consensus and peer review
    • Not all scientists will agree, but consensus reflects overwhelming support based on evidence
    • Peer review is a key mechanism to validate methods and conclusions; may be blind/double-blind
    • Example tensions: dinosaurs vs. hominids coexisting; Flat Earth claims despite overwhelming consensus that Earth is round
  • Science, prediction, and extrapolation
    • Scientists attempt to predict short-term outcomes by extrapolating from existing data
    • Caution against over-predicting to avoid loss of public trust (e.g., weather/tornado warnings)
  • The limits of science in different domains
    • Science deals with the natural world; it is not a tool for aesthetics, morality, politics, theology, or some social sciences
    • Economics and sociology include quantitative methods but are not strictly natural-sc science disciplines; some questions (e.g., eradicating poverty) may be addressed but not solved solely by science
  • Core ideas for evaluating claims in science
    • Informed skepticism and the need for reliable sources
    • Evidence-based reasoning over face-value claims
    • Contrasting coincidence, correlation, and causation
    • Distinguishing between testable hypotheses and non-testable beliefs
    • Distinguishing reasoning approaches: induction (from specific observations to generalization) vs deduction (from general principles to specific predictions)
  • Key scientific concepts explained through examples
    • Coincidence vs correlation vs causation (e.g., autistic population trends vs organic food sales; cheese and civil engineering doctorates)
    • Induction example: general frog development pattern vs observed outliers (e.g., a frog that lays eggs on a leaf rather than water, and lacks webbed feet)
    • Deduction example: a hypothetical worm-like creature is actually a caecilian, a legless amphibian; using background knowledge to interpret a new observation
    • The germ theory: diseases arise from microorganisms, not evil spirits; theories are robust explanations built from many observations
  • Misconceptions about science and certainty
    • A common myth: hypotheses become theories or theories become laws; they are distinct and not hierarchical in the way the myth suggests
    • The idea that science or technology are identical is false; science describes the natural world while technology applies science to create tools
  • Practical demonstrations of scientific thinking
    • A common misconception: all data reveal clear causal relationships; in reality, graphs can mislead if the baseline (zero) is not shown (e.g., coffee effect graph with margin of error)
    • The importance of graph design and data interpretation to avoid misleading conclusions
  • Examples of robust, testable scientific conclusions and ongoing revision
    • Alzheimer’s disease research evolving: amyloid plaques once thought to be the cause; newer evidence points to possible roles of lithium or other pathways; translating animal model findings to humans is non-trivial
    • Scientific understanding evolves with new data; rat studies may not translate to humans; time needed for consensus to shift
  • Science vs. technology
    • Science focuses on describing/explaining natural phenomena (e.g., refraction in light)
    • Technology focuses on applying science to create devices or tools (e.g., eyeglasses)
    • Both involve the same underlying science, but their aims differ
  • The interconnectedness of scientific method components
    • The scientific method is not a linear step-by-step process; many aspects interact and feed back into each other
    • Induction and deduction are complementary and both have limits; neither guarantees complete truth
  • Real-world, Earth-scale examples reinforcing scientific principles
    • Milankovitch cycles (glacial-interglacial cycles) as a driver for climate variation:
    • Precession period: T_p \,\approx\, 2.6\times 10^4\ \text{years}
    • Obliquity changes: \Delta\varepsilon \approx 3.5^\circ with values around \varepsilon \approx 23.5^\circ varying to the range [21^\circ,\; 24^\circ]\n- Eccentricity cycle: T_e \approx 10^5\ \text{years}
    • The impact of CO2 and other variables on climate forcing (contextual discussion rather than a precise formula here)
  • Summary of core principles
    • Science relies on observations, experiments, and evidence
    • It yields reliable but tentative knowledge that can change with new data
    • It emphasizes testability, reproducibility, and public verification via publication and peer review
    • It differentiates science from non-scientific belief systems and acknowledges boundaries with other domains
    • It values curiosity, openness to new ideas, and willingness to revise beliefs in light of new evidence

Hypotheses, theories, and laws: definitions and common misconceptions

  • Hypothesis
    • A tentative description or explanation of nature; an educated guess based on some data
    • Not a random guess; should be grounded in prior knowledge and observations
    • Examples: a proposed relationship to be tested in an experiment
  • Theory
    • The best possible explanation currently supported by a wide array of data
    • Not a casual or casual-use term like "just a theory"; in science a theory is highly robust and well-supported
    • Example: Germ theory of disease
  • Law
    • The best description of how something happens, usually with precise quantitative relationships
    • Distinguishes what happens and, in some cases, how it happens (depending on the law)
    • Examples: Law of falling bodies; Newton’s laws governing motion; gas laws like PV = nRT (relationship among pressure, volume, temperature, and amount of gas)
  • Deterministic vs probabilistic laws
    • Deterministic: laws that apply with certainty in ideal conditions (e.g., law of falling bodies with negligible air resistance)
    • Probabilistic: laws that describe statistical relationships with exceptions (e.g., smoking and cancer; not everyone who smokes gets cancer)
  • Important misconceptions
    • A hypothesis does not magically become a theory, which does not become a law
    • The existence of a truth in science is probabilistic and subject to revision with new evidence
  • Interaction with historical examples
    • Early 20th-century cooling hypothesis replaced by warming understanding as CO2 and other factors were recognized
    • X-ray technology: initial uses expanded with understanding of harmful effects; safety measures evolved (shielding, exposure limits)

The nature of scientific knowledge in society

  • Science as a public enterprise
    • Explanations are published and debated in journals; open to scrutiny
    • Proprietary information (e.g., a secret formula) is less typical in science; most findings are shared openly to enable replication
  • Consensus and criticism
    • Consensus is built on accumulation of evidence and peer-reviewed work
    • Unanimity is rare; consensus remains the guiding principle for established science
  • The limits of science in other domains
    • Aesthetics, morality, politics, theology, economics, and sociology involve values, beliefs, and social constructs that are not strictly testable by science
  • The role of bias and openness
    • Scientists strive for objectivity and are encouraged to revise beliefs when new data emerge
    • Open inquiry and willingness to adjust views are central to scientific integrity

Induction, deduction, and scientific reasoning

  • Induction
    • From specific observations to broader generalizations
    • Example: Frog development pattern inferred from common observations, but exceptions (folding of eggs on leaves) show that not all frogs follow the same pattern
  • Deduction
    • From a general theory or big picture to specific predictions
    • Example: A peculiar, unknown organism that resembles a worm or a snake may actually be a caecilian, a legless amphibian; using background knowledge to interpret new observations
  • Both have limitations
    • Neither guarantees correctness; new observations can require updating big-picture ideas
  • The subjectivity myth
    • Scientists strive for objectivity, but claims of bias are acknowledged; peer review and replication mitigate bias

Science and technology; examples of applied science

  • Distinction between science and technology
    • Science: describing and explaining natural phenomena (e.g., optics, refraction in light)
    • Technology: applying scientific knowledge to create devices and tools (e.g., eyeglasses)
    • The same underlying science underpins both, but they pursue different goals
  • Evidence-based interpretation of data and graphs
    • Graphs can mislead if the baseline (zero) is omitted; the example of coffee vs no-coffee scores demonstrates how margins of error and axis choices affect interpretation
    • Short-term extrapolation should be cautious and not overextend beyond the data

Practical activities and research methods in class

  • Activity 1: Penny observations
    • Task: Each team lists five observations using all senses except taste
    • Then use a magnifying glass to identify five additional observations not visible to the naked eye
    • Purpose: Demonstrate the limits of perception and how instruments extend our senses
    • Example observations (from the session):
    • Visual: penny appears worn/discolored; material looks metallic; details on the design; the penny has a Lincoln image; the overall look is dirty/crummy under magnification
    • Auditory/Touch: sound when dropped; texture on the surface; the penny is solid, not squishy
    • Shared observations include details visible only with magnification (e.g., micro-discolorations, minute inscriptions, year details)
    • Emphasizes why instrumentation (magnification) enhances observation in science
  • Activity 2: Scientifically accurate ant drawing
    • Instructions: Draw a scientifically accurate ant, not cartoonish, with correct body parts and proportions
    • Timeframe: about 10 minutes; then students share their drawings with table peers
    • Final note: on Tuesday, winners or top entries will be announced; students will be identified by last name for a subsequent event

Key numerical references and equations (summary of embedded data in the lecture)

  • Basic chemistry: water composition
    • Water formula: H_2O
  • Milankovitch cycles (climate variability drivers)
    • Precession period: T_p \approx 2.6 \times 10^4\ \text{years}
    • Obliquity (axial tilt) variation: current tilt around \varepsilon \approx 23.5^\circ, varying roughly between [21^\circ, 24^\circ]
    • Eccentricity period: T_e \approx 10^5\ \text{years}
  • Planetary classification and history
    • Pluto’s status change: from 9 planets to 8 planets becomes a matter of criteria (dwarf planet) rather than a change in the object’s nature
  • Astronomy and planetary science references
    • Dinosaurs vs. hominids timelines: dinosaurs extinct ~67\times 10^6 years ago; hominids appeared ~4\times 10^6 years ago; Homo sapiens ~2\times 10^5 years ago
  • Physics and motion (examples mentioned for educational purposes)
    • Law of falling bodies: description of motion under gravity
    • General form of motion equation under constant gravity: s = \tfrac{1}{2} g t^2, \quad v = g t, \quad a = g
  • Gas behavior (mentioned as a context for the relationship among pressure, volume, and temperature)
    • Ideal gas law (contextual reference): PV = nRT$$
  • Chemical safety and hazards mentioned
    • Carbon monoxide (CO) and carbon dioxide (CO₂) as dangerous gases in certain contexts
  • Example dates or time references in the lecture
    • X-ray discovery and early usage around the 1900s; modern safety practices implemented over time
    • 02/2008 as a cited date related to pennies (reference to pennies in circulation since 2008)
    • Saturday night deadlines for video submissions (time-sensitive requirement)

Connections to prior and real-world relevance

  • The nature of science links to everyday decision making and media consumption in the digital age; the need for reliability and skepticism in a climate of social media information
  • The historical evolution of scientific understanding demonstrates how evidence can shift public perception and policy (e.g., masks during a pandemic, dietary fats, and health recommendations)
  • The distinction between science and technology reflects how scientific knowledge translates into everyday tools and devices (vision aids, measurement instruments, etc.)
  • The activities (penny observation and ant drawing) reinforce core scientific practices: careful observation, use of instruments, and detailed description to support inquiry

Ethical, philosophical, and practical implications

  • Ethical: reliance on evidence to avoid biases and misrepresentation; openness to revision when evidence contradicts prior beliefs
  • Philosophical: science as a way of knowing vs. other worldviews; the limits of scientific explanations for aesthetics, morality, and faith-based beliefs
  • Practical: education emphasizes critical thinking, data interpretation, and responsible use of information sources; the importance of proper data visualization to avoid misleading conclusions