Nature of Science and Technology Study Guide for Scientific Investigation

Definition of Science: Science is a particular way of knowing about the world. According to the National Academy of Sciences, scientific explanations are strictly limited to those based on observations and experiments that can be substantiated by other scientists. Explanations that are not grounded in empirical evidence are categorically excluded from the domain of science.
Scientific Knowledge: Science is fundamentally based on experimentation. Because of this, our collective understanding is dynamic; it is constantly being built upon and refined as new findings emerge.
Key Scientific Terms:
- Fact: An objective and verifiable observation.
  - Example: Water boils at $100\,^\circ\text{C}$ .
- Principle: A statement based on repeated experimental observation that describes a specific aspect of the world.
  - Example: The Greenhouse Effect.
- Law: A broad concept or principle that explains HOW things happen in nature. Laws describe consistent patterns and are often accepted as facts.
  - Examples: Newton’s Laws of Motion, Boyle’s Gas Laws, Law of Conservation of Mass.
- Theory: An explanation of an observed phenomenon. It organizes facts and research from various scientists to explain WHY something happens. A theory NEVER becomes a fact or a law.
  - Example: Evolutionary Theory.

Observations: Descriptions of something you can see, smell, touch, taste, or hear. Observations must be objective and are not opinions.
- Example: "The ground is wet."
Inferences: A guess or assumption about an object or outcome based on observations. Multiple inferences can be made from a single observation.
- Example Inference 1: "It rained."
- Example Inference 2: "Someone was watering the plants."
Qualitative Observations: These describe qualities.
- Examples: Green liquid, large hole, sour taste, sweet smell.
Quantitative Observations: These use numbers to measure something.
- Examples: $4\,\text{feet long}$ , $6\,\text{legs}$ , $7.2\,\text{grams}$ , $100\,\text{mL}$ .

Precise: Refers to how close measurements are to each other. Precision indicates consistency and specificity in data collection.
Accurate: Refers to how close a measurement is to the correct or accepted value. Accuracy indicates correctness.
Measurement Standard: When recording data, always provide the most specific reading possible on the instrument and then estimate one more decimal place.

Purpose/Objective: A statement derived from background research that clearly defines the question the investigation intends to answer.
Hypothesis: A testable prediction based on observations that describes a cause-and-effect relationship between variables. It is more than a mere guess.
- Hypothesis Format: "If (Independent Variable), then (Dependent Variable)."
Independent Variable (IV): The variable that the experimenter deliberately changes or manipulates.
- Often represented on the X-Axis of a graph.
- It should be the only difference between experimental groups.
- Running Experiment Example: If testing if drink type affects race speed, the IV is the type of drink.
Dependent Variable (DV): The variable that changes in response to the independent variable.
- Represented by the data collected; what is being measured.
- Often represented on the Y-Axis of a graph.
- Running Experiment Example: The DV is the time it takes to run the race.

Materials List: A bulleted list of everything needed for the experiment. It must include specific amounts and brands where necessary.
Procedures: A numbered list of every step taken. Steps should start with action words. It must be written with enough detail that another person could replicate the experiment exactly.
Experimental Group(s): The groups being tested in the investigation.
Control Group: The group used for comparison. This is the "normal" group that does not receive the experimental treatment.
Constants: The aspects of an experiment that are kept consistent across all trials. This ensures that any difference in the DV is caused strictly by the IV.
- Example for running experiment: Runners should lead the same lifestyle (same age, gender, breakfast, training, shoes).
Repeated Trials: Essential for ensuring results are not due to chance, eliminating errors, and ensuring data precision.

Results: Data should be collected in an organized form (e.g., a data table) and presented clearly through graphs.
Analysis: Statements should only reflect what the data shows. This includes highlighting trends or patterns and discussing potential errors.
Conclusions: An explicit statement regarding whether the hypothesis was supported or rejected by the data.
- Constraint: Data does NOT "prove" or "disprove" a hypothesis; it either supports it or fails to support it.
- Implementation: Describe real-world applications for the learned information.

Science vs. Technology:
- Science: Focused on the advancement of knowledge. It answers questions based on observations.
- Technology: Focused on the advancement of society. It solves problems based on human needs. It is the application of scientific discoveries to meet goals through products or processes.
- Engineering: The process of applying scientific and mathematical principles to solve specific problems.

Problem Identification: Clearly define the problem or the need.
Solution Design: Brainstorm, research, sketch, and select the best design. This must occur within specific constraints:
- Cost effectiveness.
- Time effectiveness.
- Materials: Considering availability, durability, and environmental impact.
- Note: A perfect design is impossible, but the goal is for benefits to significantly outweigh risks.
Implementation: Building and testing the design while making continuous improvements.
Evaluation: Determining if the problem was solved and if all project constraints were met.