1. Outline Go over the reading: summarize reactions Intro talk: the scientific method –Concepts and frameworks we’ll use Examples from a few readings An overview of today’s lab Prep work and logistics for the lab Assignments, schedule changes, etc

2. Science A framework for solving problems and making sense of the world around you

3. New College Problem-based seminars Science occupies an embattled, problematic place in our world Conflicts and controversy over the politics of science are frequent and require scientific literacy Hands on experience with the scientific method

4. Points to take away from the reading in Angier: intro Science: it’s not just for little kids Misunderstood and embattled, but useful –No $, no fame, yet the engine of society Thinking scientifically is underrated

5. Points to take away from the reading in Angier: Ch2 Science: not just a body of facts Universality of the scientific method Scientists believe there is an objective reality that can be unmasked through tools of science Wonder can be cultivated Quantitative thinking can be helpful Facts, not truth, and science is not opinion

6. Points to take away from the reading in Angier: Ch2 Bias and bad data are our enemy –Experimental design and controls –Blinding studies Approaching the same problem via multiple routes is often the best way and gives the findings credibility Science is based on defending your data and conclusions in a peer group of others

7. Points to take away from the reading in Angier: Ch2 Scientists think in grey tones and often arguments are not well translated to the popular media Scientists are fixated on the unknown and debate: they are attacked on these grounds by non-scientists who fail to understand what science is all about We are often superstitious creatures who believe things with no evidence; most scientists yield only to scientific arguments

8. SO

9. What does scientific literacy mean? Being able to sort out what constitutes science and what does not –Good science versus pseudoscience or bad science Comfort with common terms and concepts involved in the scientific method –Fluency in scientific language (download vocabulary) The ability to explicitly design, conduct, and communicate a science experiment Attaining an understanding and appreciation of uncertainty and conflicting viewpoints –Non-dualistic thinking –Understanding of science as a process Scientific thinking is applicable to everything

10. Science as process The scientific method is a way of approaching the world around us Not mystical or specialist Usually more questions arise than are answered – more hypotheses are generated Inherently iterative You have to expect that you will be proved wrong. We are all blind men describing elephants.

11. Hypotheses Usually defined as “an educated guess” –What is that? –A question that arises from observing the world around us Often includes inherent bias –Sometimes no one asks the right questions or only asks questions to which they already think they have the answer Can be the product of inductive or deductive reasoning –Inductive reasoning is generalizing –Deductive reasoning is Must be falsifiable (Karl Popper) and testable –Useful in determining what hypotheses are scientific (or are political, pseudoscientific, etc)

12. Scientific method Approximately 11 Steps Process is repeated many times Can NEVER prove a hypothesis –Can only reject many, leaving one as best supported by the data –“Scientific Proof” is a common fallacy –Associations don’t prove causation –FACTS not TRUTH

13. Scientific method - Steps 1-5 Observe or suspect pattern Posit significance of observed difference Create question to explain pattern Create testable hypotheses Design experiment

14. Collect data (descriptive stage) Analyze data, primarily using statistics Evaluate hypotheses, accept or reject them Make conclusions based on data Note problems in current work Predict future directions for research The process is the structure for write-ups Scientific method - Steps 6-11

15. Parts of a scientific report Title [Abstract - an overall summary] Introduction - background, question, H a s Methods - what we did Results - what we found, graphs, summarized data Discussion - interpretations, predictions References - who we cited Document on course website!

16. Scientific Communication Written report –Traditional Oral presentation –Commonly used for preliminary presentation of work to get feedback before writing it up Poster –Visual summary of work - used at conferences Web page –Can use a written report & make it interactive

17. Experiments Independent variable: one thing that changed (measured) Dependent variable: outcome (measured) –This language comes from math: y=mx+b Usually experiments must be repeatable –Some are not repeatable or even ethically repeatable Always use controls – snake and tadpoles Ethics and experimental design

19. Key concept: reasoning Inductive reasoning: –Generalizing: This floor is hard, all floors must be hard Deductive reasoning: –(Coming to a conclusion based on premises: all birds have feathers, an ostrich is a bird, so all ostriches have feathers) Key in hypothesis generation and in drawing conclusions from work Often extensions are not valid

20. Key concept: errors in analysis Type 1 error: "false positive": the error of rejecting a null hypothesis when it is actually true; observing a difference when in truth there is none. Type 2 error: "false negative": the error of accepting a null hypothesis when the alternative hypothesis is the true state of nature. In other words, this is the error of failing to observe a difference when in truth there is one.

21. Key concept: Occam’s razor AKA Law of Parsimony –The simplest explanation tends to be the best Often also the least entertaining Means that we’re better off not using our imagination too much when trying to explain natural phenomena Simpler theories are often easier to test, so science is biased in favor of them (K.P) Einstein: OR doesn’t mean simplification is best. Things should be made as simple as possible, but no simpler

22. Key Concept: the precautionary principle The precautionary principle states that when science is extended and there are risks of irreversible risks to human health or the environment, the burden of proof is on the doer. Species extinction, Global warming, GMOs, Public health, Persistent or acute pollution (endocrine disruptors, asbestos), Food safety (CJD), Artificial life, new designer molecules, etc

23. Key concept: Non-Western science Sometimes pseudoscience, often not Ethnobotany, ethnopharmacology, ethno- etc. May be linked with superstition or religion Often provides real insight that can be co- opted by university-trained scientists from rich countries –Inoculation/vaccination –Geography Under the radar

24. In-class readings

25. Identify hypotheses, explain experimental methods and analyses, and discuss outcomes Were controls used? How? How are these experiments similar/different? How did this study contribute to the creation of new knowledge?

26. Agriculture lab Woman’s oldest science “Trial and error” and logic are always used –Observing what works and what doesn’t –Often leads to spurious conclusions Like hanging bags of water on the wall Mangoes and sugar We’ll be using our basic knowledge of the scientific method to explore the effect of soil composition on crop development

27. Background NPK Various materials add these macro- nutrients –We have a few on hand here –Blood meal, bone meal, greensand –Composted cow doo doo (scientific term) We want to know whether adding these things to the soil will achieve a measurable increase in plant growth

28. Experimental design Three plots, all with different soil types Unimproved soil Soil with composted manure Soil with composted manure and NPK additives Outcome of interest: plant development

29. Hypothesis We want to know____________________

30. Materials and methods Tools we need How do we intend to go about answering this question? –Data collection plan –Data analysis plan

31. Results Pooled class data Graphs and tables Simple statistics

32. Discussion Contextualizing results, explaining sources of error, etc

33. Conclusions What did we find? Why does it matter?

34. Logistics Need 6 teams of 3 people Each team visits the garden over the next 6 weeks to record data We’ll analyze data all together and each person writes his or her own lab report

35. Need volunteers for these times Week 0: today Week 1: Sept 3-9 Week 2: Sept 10-16 Week 3: Sept 17-23 Week 4: Sept 24-30 Week 5: Oct 1-7 Week 6: Oct 8-14 Visit at your own discretion sometime that week