Nature of Science

2. Nature of Science “Science is a particular way of knowing about the world. In science, explanations are limited to those based on observations and experiments that can be substantiated by other scientists. Explanation that cannot be based on empirical evidence are not part of science.” • The National Academy of Sciences

3. Nature of Science • Science is based on experimentation • The development of an experiment tends to follow the Scientific Method • Ask a question • Conduct background research • Construct a hypothesis • Test your hypothesis in an experiment • Analyze Data • Draw conclusions and communicate them

4. Ask a question – often based on observations • Observation: Description of something you can see, smell, touch, taste, hear • NOT an opinion!! (must be objective) • Example: • The ground is wet • Inference: A guess about an object or outcome based on your observations • You can make many inferences from a single observation • Example: • It rained. • Someone was watering the plants

6. Ask a question – observations are either… • Qualitative Observation: describes qualities • Examples: • Green liquid • Large hole • Sour taste • Sweet smell • Quantitative Observation: uses numbers to measure something • Examples: • 4 feet long • 6 legs • 7.2 grams • 100 mL

8. Considerations for Quantitative Data Quantitative data must be… • PRECISE = how close your measurements are to each other (think consistent or specific) • ACCURATE = how close your measurement is to the correct/accepted value (think correct) Always give the most specific reading on your instrument, then estimate one more decimal place

9. Precise and Accurate Precise but not Accurate Accurate but not Precise Not Accurate or Precise

10. Conduct background research – define a Purpose/Objective • The GOAL of scientific investigations is to answer a question • Observations  Questions  Research (what has already been found?)  Purpose • Purpose/Objective is a statement that clearly shows what question you are trying to answer in your investigation

11. Construct a Hypothesis • Hypothesis: A testable prediction based on observations (more than a guess!!) that describes a cause and effect relationship between variables Format for a Hypothesis: “IF (IV) then (DV) “ IV = Independent variable = Cause DV = Dependent variable = Effect

12. Defining Independentand DependentVariables • Independent Variable: (IV) what the experimenter will deliberately change or manipulate in the investigation • The X-Axis on a graph • It is the ONLY thing different between different experimental groups • Ex. You want to do an experiment to see if what you drink before a race affects how quickly you run. • What is the IV?

13. DefiningIndependentand Dependent Variables • Dependent Variable: (DV) what changes in response to the independent variable • The Y-Axis on a graph • Usually represented by the data you collect in an investigation; what is measured • Ex. Recall the running experiment. • What is the DV?

14. Test your hypothesis in an experiment- Materials • What will you need to conduct the experiment? • Include amounts • Include brands, if important • Be as specific as possible! • Write as a bulleted list

15. Test your hypothesis in an experiment- Procedures • Write out every step that was taken • Start with an action word • Include every step so that someone could replicate the experiment • Make this a numbered list When designing experimental procedures you must ALWAYS consider… • Experimental Group: groups that are being tested • What is the experimental group in the running example?

16. When designing experimental procedures you must ALWAYS consider… • Control Group: group used for comparison with your experimental groups. This is the “normal” group • What is the control group in the running example? • Constants: the aspects of an experiment that are held constant/consistent • Ensures that all aspects of trials are identical, except for the IV • Ensures that any difference measured in the DV is caused only by the IV • Ex. All runners should be the same age, gender, same breakfast, same training, same shoes, etc.

17. When designing experimental procedures you must ALWAYS consider… Repeated Trials to: • Ensure the results aren’t due to chance • Eliminate any errors • Ensure the data is precise

18. Analyze Data – Results and Analysis Results • Collect data in an organized form during an investigation (ex. Data Table) • Present data in a graph Analysis • Only make statements about what the data shows • Do NOT state in analysis whether your hypothesis was “right” or “wrong” • Include any errors you made

19. Draw conclusionsand communicate them • Make an explicit statement about whether your hypothesis was supported or rejected by your experimental data • Data may support your prediction • Data may fail to support (reject) your prediction • NOTE: Data does NOT prove/disprove • State the real world application.