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  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. Scientific method - Steps 6-11 • 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

  15. Parts of a scientific report • Title • [Abstract - an overall summary] • Introduction - background, question, Has • 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

  18. 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

  19. 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.

  20. 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

  21. 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

  22. 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

  23. In-class readings

  24. In-class readings • 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?

  25. 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

  26. 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

  27. 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

  28. Hypothesis • We want to know____________________

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

  30. Results • Pooled class data • Graphs and tables • Simple statistics

  31. Discussion • Contextualizing results, explaining sources of error, etc

  32. Conclusions • What did we find? Why does it matter?

  33. 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

  34. 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