Comprehensive Intro to Biology and the Scientific Process – Study Notes

Opening Questions

  • Is it life? Consider a future explorer with a probe returning unidentified organic-looking microscopic objects.
  • How would you determine if these objects are living organisms?
  • What properties would you require before you call something life?

What is Biology?

  • Biology is the scientific study of life.
  • Biologists recognize life through a series of properties shared by all living things.
  • An object is considered alive if, and only if, it displays all of these properties.

Properties of living things

  • Order: Each living thing has a complex but well-ordered structure.
  • Energy and Matter Processing: Every organism takes in energy, converts it to useful forms, and expels energy.

Additional properties

  • Reproduction: All organisms reproduce their own kind.
  • Growth and development: Information carried by genes controls the pattern of growth in all organisms.

Response and adaptation

  • Response to the environment: All organisms respond to changes in the environment. Many responses help keep an organism’s internal environment within narrow limits.
  • Evolutionary Adaptations: Traits evolve over countless generations by reproductive success of individuals with heritable traits best suited to their environments.
  • Example: The broad thin ears of an elephant are an evolutionary adaptation to dissipate heat.

Viruses: alive or not?

  • Using the living criteria, decide if a virus is alive.
  • Virus facts:
    • A virus is highly ordered.
    • Viruses can evolve over time.
    • Although viruses can infect many organisms, they cannot reproduce on their own.
  • Question: Would you consider a virus alive?

Are viruses alive? (continued)

  • A virus doesn’t have ALL of the properties of life.
  • The idea is not settled, but many biologists agree viruses are not alive.
  • In science, viruses are viewed as existing in a state between living organisms and nonliving chemicals.

Levels of biological organization

  • The biosphere: all life on Earth.
  • An ecosystem: the living and nonliving components.
  • A population: a group of interacting individuals of one species.
  • A community: all interacting populations in an ecosystem.
  • An organism: a single living being.
  • An organ system: a group of organs that work together.
  • An organ: multiple tissues that cooperate to perform a task.
  • A tissue: an integrated group of similar cells that work together.
  • A cell: the fundamental unit of life.
  • An organelle: a component of the cell that performs a specific function.
  • An atom: the fundamental unit of matter.
  • A molecule: a group of atoms bonded together.
  • Note: Image reference “100x” indicates magnification level for some structures (e.g., tissue/cell components).

Unity and diversity in life

  • Questions: What do all living things have in common? How do living things differ?
  • Explore features common to life and the ways life differs.

Major themes in biology

  • Several major themes run through biology to help organize and understand information.

Life requires energy and matter processing

  • Living things regulate the transformation of energy and matter.
  • All cellular activities require energy and matter to proceed.
  • The sun provides the energy that drives nearly every ecosystem.

Interconnections across levels

  • Life is studied from microscopic to global scales.
  • Emergent properties appear at higher levels that are absent in lower levels (e.g., a cell can reproduce; its parts cannot).

Structure and function are linked

  • Structure (shape) and function (what it does) correlate across levels.
  • Example: The millions of tiny sacs (alveoli) in lungs provide a structure that enables gas exchange.

Information flow across biology

  • Information in genes is encoded in a universal chemical language shared by all organisms.
  • Many inherited diseases result from gene mutations.
  • Example: Angelina Jolie underwent a preventive double mastectomy after learning she carried mutations in breast cancer genes.

Evolution as the unifying theme

  • The theory of evolution through natural selection explains the descent with modification from ancestral species to modern forms.
  • It helps explain common characteristics across life and phenomena such as antibiotic resistance.

Inquiry and science—the tall cookies metaphor

  • The secret to taller cookies can be explored through inquiry.
  • Consider whether ingredient changes can produce taller cookies; this illustrates how hypotheses are formed and tested.

Inquiry is fundamental to science

  • Science investigates the natural world through inquiry: seeking information, evidence, explanations, and answers.
  • Biologists use the process of science to study life.

Scientific investigations begin with observations

  • A hypothesis is a proposed explanation to a question that can be investigated.
  • Example: Observations that some cookies are taller than others lead to a question about which ingredient causes height.
  • Hypothesis example: Swapping cake flour for all-purpose flour will yield taller cookies.

The scientific method is a flexible process

  • The method provides a “recipe” for understanding the natural world.
  • Experiments generate data that may support or refute a hypothesis.
  • The process is not strictly linear; it flows in cycles.
  • Example: An experiment compares cookie height with cake flour vs. all-purpose flour.

Heart of scientific inquiry: hypotheses and data

  • Hypotheses are tested by collecting data (observations, measurements).
  • Phases of inquiry: Exploration, Testing, Communication, Outcomes.
  • Exploration: observe nature, ask questions, read scientific literature, seek information.
  • Testing: form hypotheses, make predictions, run experiments, gather data, analyze data, draw conclusions.
  • Communication: share data, obtain feedback, publish papers, attend meetings, replicate findings, build consensus.
  • Outcomes: build knowledge, solve problems, develop new technologies, inform policies, benefit society.

The process of science: a diagrammatic view

  • Phases include:
    • EXPLORATION: Observing nature; asking questions; reading literature; seeking information.
    • TESTING: Forming hypotheses; making predictions; running experiments; collecting data; analyzing data; drawing conclusions.
    • COMMUNICATION: Sharing data; obtaining feedback; publishing; attending meetings; replicating findings; building consensus.
    • OUTCOMES: Building knowledge; solving problems; developing technologies; informing policies; benefiting society.

Opening questions and everyday observations

  • Observations come from the natural world around us; you can observe in everyday life and in class commutes.

Hypothesis testing versus everyday life

  • A good hypothesis is testable and falsifiable.
  • Observations lead to a hypothesis; scientists do not try to prove hypotheses, they test whether data support or do not support them.
  • Definition reminder: a hypothesis is a proposed explanation that can be investigated.

Experimental vs observational testing

  • A test of a hypothesis can be experimental (conditions controlled) or observational (investigate aspects not easily controlled, e.g., ecology).

Everyday use of hypotheses

  • People use hypotheses to solve problems in daily life, e.g., why a phone doesn’t respond when power button is pressed.
  • The hypothesis might be: the battery ran down. An experiment (or observation) is used to test this.
  • Conclusions may support or refute the hypothesis; continue formulating new hypotheses and testing until achieving the desired outcome.

Hypothesis vs theory

  • A hypothesis is a tentative explanation; a theory is a well-substantiated, broad explanation that explains many observations.
  • The theory of evolution by natural selection is a core unifying theme in biology.
  • Example: Physical adaptations evolve over many generations due to reproductive success of individuals with beneficial heritable traits.

Comparing hypothesis and theory (summary)

  • Hypothesis: narrow in scope, testable, falsifiable, not necessarily proven, may be refutable by new evidence.
  • Theory: broad in scope, well-supported by evidence, testable and falsifiable, never proven false, can be revised with new data.
  • Examples provided for each: elephant ears (hypothesis) vs broader statements about adaptive evolution (theory).

Facts and scientific knowledge

  • A fact is verifiable and considered objectively true based on current evidence.
  • Facts and repeatable experimental results are prerequisites of science, but accumulating facts is not the primary goal.
  • Example: elephants are the largest land animals.

How theory is used in science vs everyday language

  • Everyday use: theory often means conjecture, speculation, or opinion.
  • Scientific language: theory is well supported, testable, and based on objective data.
  • It is inappropriate to dismiss a scientific theory as “just a theory.”

Controlling variables in hypothesis testing

  • In a controlled experiment, only one variable is changed at a time (the independent variable) to test its effect.
  • The dependent variable is the response being measured.

Independent, dependent variables, and controls

  • Independent variable: what you manipulate as a potential cause.
  • Dependent variable: the response or effect under investigation.
  • A control group establishes a baseline for comparison.
  • Negative control: no change expected (baseline).
  • Positive control: a change is expected (to confirm the system can respond).

Reducing bias: blind experiments

  • A blind experiment withhold information from participants (single-blind) or from both participants and experimenters (double-blind) to reduce bias.
  • The placebo effect: a patient feels better after believing treatment was given, even if none actually was.

Cookie-tasting opening question (illustrative example)

  • In a taste test of two recipes, questions arise about which recipe is superior; this illustrates experimental design and statistical interpretation.

Data communication in science

  • Scientists communicate data using graphs, tables, and charts.
  • Tables organize data; graphs summarize and compare information visually.
  • Types of graphs:
    • Bar graphs: compare categories; error bars indicate uncertainty in differences.
    • Line graphs: show continuous changes; y-axis is the dependent variable, x-axis is the independent variable.
    • Pie charts: show numerical proportions; the whole pie equals 100%.

Interpreting data from graphs

  • Example: a pie chart interpreting lung cancer diagnosis stages (local vs spread) is used to discuss outcomes and potential improvements.

Types of scientific studies

  • Hypothesis-driven controlled experiments test a hypothesis directly.
  • Observational studies examine subjects without manipulation (field data, ecological hypotheses, human health pragmatics).
  • Epidemiologists measure links between lifestyle and health over long periods (observational).
  • Clinical trials are controlled experiments using humans; subjects are randomly assigned to experimental or control groups; controls may receive a placebo.

Epidemiology and clinical trials examples

  • Example: an epidemiological study followed 18,000 people for seven years to assess insulin pump use and risk differences for heart disease and death; answer choices include A) 5% B) 15% C) 50% D) 75% E) 100%.
  • Clinical trial example: Garg et al., randomized controlled trial, NEJM 2017.

Critical thinking and evaluating claims

  • Critical thinking is essential to evaluate scientific claims; it involves unbiased analysis and assessment of information.
  • Recognize pseudoscience.

Pseudoscience vs science: features

  • Features of science vs pseudoscience:
    • Adheres to established, well-recognized scientific methods vs does not adhere to generally accepted processes of science.
    • Results are repeatable vs results are not duplicable or rely on single individuals or opinions.
    • Claims are testable and disprovable vs claims are unprovable or untestable and rely on beliefs.
    • Open to outside review vs rejection of external review or contradictory evidence.
    • Multiple lines of evidence vs overreliance on a small data set without exploring underlying causes.

Examples of pseudoscience

  • Fortune-telling: results are not repeatable; different soothsayers give different results for the same data.
  • Personality trait predictions from skull measurements do not hold up to independent review.
  • ESP claims have not been demonstrated in controlled settings.

Evaluating scientific claims critically

  • Key considerations:
    • Sample size: how many subjects per group.
    • Control group: increases confidence in differences observed.
    • Reproducibility: other groups should reproduce results.

What’s in the news?

  • Regularly review a current science article to assess whether it includes references to sample size, control groups, or reproducibility.

Sources and reliability

  • Primary source: original material presented by the researchers; peer-reviewed sources are preferred.
  • Secondary source: descriptions or reviews of primary sources.
  • Wikipedia is a common starting point but can be edited by anyone.

Peer review and reliability

  • Peer review is the evaluation of work by impartial, qualified outside experts.
  • A study published in a peer-reviewed journal is generally considered the gold standard for validating scientific work.

Recognizing reliable sources

  • Check currency: is the information up-to-date?
  • Primary vs secondary: is the source original material?
  • Author credentials and potential conflicts of interest.
  • Citations and reproducibility: are experiments described with enough detail for replication?
  • Peer reviewed? Is the source unbiased? Is the intent clearly stated and valid?

References

  • Simon, E. J. (2019). Biology: The Core. Pearson.