1. Scientific Methods and Terminology

2. Scientific methods are The most reliable means to ensure that experiments produce reliable information in response to a specific question. The steps taken to answer a specific question.

3. STEPS – may include Observations Form questions Make hypotheses Design an experiment Analyze results Make conclusions Publish Findings

4. OBSERVATION In contemplating phenomenon that occur in nature, questions arise. Humans have the need to answer these questions – thus experimentation occurs. To make an observation is to examine something using the senses or instruments to get information.

5. Questions What questions do you have about your observations of the natural world? Why is the sky blue? What causes disease? What is a cure for cancer? Why can you only have a particular virus once?

6. Hypotheses After carefully researching topics that relate to the question- hypotheses can be formulated. Scientific researchers usually have several working hypotheses and at least one null hypothesis. A hypothesis is A logical but unproven explanation for a given set of facts. Developed through observations or previous experiments For learning purposes, may be an If/then statement (although scientists do not write If/then statements). Ex. If the plant is not watered, then it will die.

7. The Null and Alternative Hypothesis A null hypothesis (H 0 ) presumes that the independent variable has no affect on the experimental group. The alternative or research hypothesis/ hypotheses (H 1, H 2 H 3,... ) predicts that the manipulation of the independent variable does affect the experimental group.

8. Experiments Test a hypothesis by collecting information under controlled conditions. There are two groups in an experiment Control group – all conditions are kept normal for the test subjects. Experimental group – all conditions are kept the same as the control group except for the single independent variable being tested.

9. Variables Controlled Variables – conditions kept the same for both the control and experimental groups (AKA constants). Independent variable – experimental variable- the variable being tested in the experiment to determine if it affects something else. Dependent Variable – the changes that result from the testing of the independent variable. The independent variable is “what the scientist is ‘doing’ to the experimental group and the dependent variable is “what happens to the experimental group as a result of what was done.” The dependent variable depends on the independent variable.

10. Ex. You want to test the effect of light on the growth of tomato plants. 1.What is the independent variable? 2.What is the dependent variable? 3.What are the controlled variables?

11. Data Quantitative – numerical counts or measurements Scientific measurements are always metric Reported in graphs or tables Qualitative (descriptive) – written descriptions.

12. Data lends support for or against the hypotheses. When a hypothesis is supported over time by many investigations it becomes a theory A theory is an explanation for natural phenomena that has been tested many times and confirmed by many scientific experiments. Ex. Theory of Inheritance Facts of nature generally known to be true are laws (usually expressed mathematically) Ex. Law of Gravity

13. Designing Experiments The Purpose The purpose clearly states the phenomenon or question you plan to investigate. Your purpose should guide your experimentation and help keep you on track.

14. Hypotheses The next step is to formulate hypotheses. A hypothesis is your informed prediction about the outcome of your research. Your experiment should include both the alternative and null hypotheses.

15. Variables You should clearly state the variables in your experiment. These include dependent, independent, and controlled variables (sometimes called constants).

16. Procedure Raw data by itself is meaningless unless people know how it was collected. You should describe the method you followed to obtain your data as well as the materials and equipment used so that anyone could reproduce your experiment at a later date.

17. Results/ Data This includes all the data you collect from your experiment. All data, whether it fits with what you expected or not, must be recorded. Your results should be presented in the clearest way possible. Quite often this will include graphs and charts to show trends and relationships.

18. Conclusions The conclusion must be based on the results of your experiment and should explain how you reached that conclusion (you must include evidence). It should also include whether or not your data supports the alternative hypothesis or if you fail to reject the null hypothesis.

19. Communicate The last step is to communicate the results with others. Scientists publish their research in journals – an example is The New England Journal of Medicine.

22. Key Features of “Good” Experimental Design 1.The question must be testable using scientific investigative techniques. 2.The investigation must be designed such that the hypotheses can be distinguished.

23. 3. The experiment must provide enough data for statistical analysis. (Multiple trials and/or large sample size). 4. The experiment must be controlled. (Variables other than the independent variable must be constant for the experimental and control groups.) 5. The experiment must provide data. 6. The experiment should only test ONE independent variable.

24. 7. The procedure should be clear and complete. 8. The experiment must include a control group for comparison. 9. The experiment can be reproduced by other scientists to provide similar results.

25. Reasoning In logic, we often refer to the two broad methods of reasoning as the deductive and inductive approaches. Arguments based on experience or observation are best expressed inductively. Arguments based on laws, rules, or other widely accepted principles are best expressed deductively.

26. Deductive Reasoning Deductive reasoning works from the more general to the more specific. Sometimes this is informally called a "top-down" approach. We might begin with thinking up a broad hypothesis about our topic of interest. We then narrow that down into more specific hypotheses that we can test. We narrow down even further when we collect observations to address the hypotheses. This ultimately leads us to be able to test the hypotheses with specific data -- a confirmation (or not) of our original predictions.

27. "Deductive reasoning" refers to the process of concluding that something must be true because it is a special case of a general principle that is known to be true. For example, if you know the general principle that the sum of the angles in any triangle is always 180 degrees, and you have a particular triangle in mind, you can then conclude that the sum of the angles in your triangle is 180 degrees. Deductive reasoning is logically valid.

28. Inductive Reasoning Inductive reasoning works the other way, moving from specific observations to broader generalizations and theories. Informally, we sometimes call this a "bottom up" approach

29. In inductive reasoning, we begin with specific observations and measures which are used to detect patterns and regularities, formulate some tentative hypotheses that we can explore, and finally end up developing some general conclusions or theories.

30. Inductive Reasoning is the process of reasoning that a general principle is true because the special cases you've seen are true. For example, if all the people you've ever met from a particular town have been very strange, you might then say "all the residents of this town are strange". That is inductive reasoning: constructing a general principle from special cases.

31. Inductive reasoning is not logically valid. Just because all the people you happen to have met from a town were strange is no guarantee that all the people there are strange.

32. Learning Objectives At the end of the unit on scientific methods, you should be able to: 1.Identify questions that could be answered with scientific research.

33. 2. Explain experimental protocol by defining/explaining: Variables – independent, dependent, controlled Data collection methods The role of technology and mathematics. Result verification (large sample size and/or repetitions). 3. Design and conduct a scientific investigation. 4. Formulate and revise a scientific explanation using evidence. 5. Distinguish between deductive and inductive reasoning.