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Applied Bayesian Statistics in Biology

by: Marcella Lebsack

Applied Bayesian Statistics in Biology BIOL 6309

Marketplace > Texas Tech University > Biology > BIOL 6309 > Applied Bayesian Statistics in Biology
Marcella Lebsack
GPA 3.81

Richard Strauss

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Richard Strauss
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This 5 page Class Notes was uploaded by Marcella Lebsack on Thursday October 22, 2015. The Class Notes belongs to BIOL 6309 at Texas Tech University taught by Richard Strauss in Fall. Since its upload, it has received 32 views. For similar materials see /class/226497/biol-6309-texas-tech-university in Biology at Texas Tech University.


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Date Created: 10/22/15
Statistical Inference amp Analysis Biol 6309 Richard E Strauss Statistics The typical View of statistics Somebody told me that I needed this course so let s get it out ofthe way so thatI can get on with my life Statistics is not a set of rules it is a philosophy oflife 7 Statistics is the study of variation and uncertainty in particular statistics is the study of how to make reasonable decisions and predictions in the face of uncertainty Applied statistics is a set of methods and procedures based on an underlying theoretical discipline mathematical statistics As in other applied vs basic elds there is no right way or wrong way of doing things just appropriate and inappropriate defensible and indefensible 7 There s only one rule of how to do statistics which is basically the rule of how to do science you can do whatever you like but you must be able to defend it 7 Ignorance is not an adequate defense 7 Appeal to authority is not an adequate defense A person using statistics has to be part detective part lawyer 7 Detective searches for clues and uncovers the patterns 7 Lawyer builds a formal case that will stand up in the court of peer review Statistics is not something you do at the end of a study 7 Here are m data now how do I anal ze them Rather statistics must be an integral part of the way in which a study is designed 7 What are my biological questions and can they be translated into statistical hypotheses If so how What will be the most appropriate statistical tools for answering my questions and What assumptions must I meet in order to be able to use those tools 7 What are to be the data andhow are they to be collected How can I best avoid Wasting my time and resources What are the minimum sample samples that I will need and how many replications can I get bywith Even ifI collect all ofthe dataI can possibly collect can I actually answer the questions Statistics ier t the icing it s the recipe for the batter Why statistics The brain is a very ef cient patternrecognition system 7 Signaltonoise problem 7 We are adept at finding signals and patterns in a very noisy world Constellations Bands of color in rainbow Faces 7 Association learning associating causal connections between A and B Clouds cover the sun and the air becomes cool The presence of heat causes water to boil Apply manure increase plant growth 7 We learn to expect patterns and associations Clusters in data Correlations among variables Why statistics Problem if you scan enough noise you ll eventually nd a signal or pattern whether it s there or not 7 Coincidence 0 360 million 7 eoi 1e in the US 0 1inami11ion occurrence happens on average 360 timesday 7 False association learning A appears to be connected to B but it s not Baseball player doesn t shave and his a home run Aunt Harriet drinks extract of seaweed and her cancer goes into submission Face ofthe Virgin Mary appears on a grilled cheese sandwich and it s auctioned for 28000 7 Anecdote Statistical Quotes of the Day The secret language of statistics so appealing in a factminded culture is employed to sensationalize in ate confuse and oversimplify D uff How toLie with Statistics 1954 Most scientists need all the help they can get to prevent them from making fools of themselves by claiming that their favorite theory is substantiated by observations that do nothing of the sort The main function of tests of signi cance is to prevent people from making fools of themselves D Colquhoun Lectures on Statistics 1971 It is to prevent the reporting of nonsense that we apply hypothesis testing statistics not to prove that nonsense is sense I L Phillips Jr How to ThinkAbout Statistics 1996 It s remarkably easy to use statistics to mislead 7 Sometimes done intentionally to mislead others Politics There was a 300 increase in last year Advertising Clinical studies prove 7 But statistics eann ot be used to prove hypotheses only to reject th em 7 Hypotheses are supported only to the extent that they re not rejected Not guilty is not the same as innocent There are three kinds of lies lies damned lies and statistics LeonardHenry Courtney But it is easier to lie without them Mosteller In science lying is more often done unintentionally misleading ourselves as well as others by 7 being misled by assumptions that aren t true 7 trusting summary statistics without looking at plots and other graphics 7 usmg statlstlcal methods blased 1n favor of the expected outcome 7 discarding outliers and intermediates without sufficient justification 7 using tests of insufficient power 7 selectively interpreting results or misinterpreting results e g by accepting null hypotheses 7 overreducing data too soon e g to means and standard deviations only or to categories 7 reporting the output of computer programs without understanding how the results are obtained or what they mean Statistical Quotes of the Day Statistical analysis is NOT a daunting task anymore You don t need to know which test is right for your data Simply open the Advisor Wizard and then answer a few questions about your data and your research project SigmaPlotll suggests the appropriate statistical test and checks your data against the test s underlying assumptions If you data violates any of these assumptions the Advisor Wizard suggests another test 7 Advertising brochure for SigmaPlotl l 2008 It is important to understand what you can do before you learn to measure how well you seem to have done it 7 John Tukey 1977 Data analysis is an aid to thinking and not a replacement for it 7 Richard Shillington 2003 A statistics course taught well is a thing of lasting value A statistics course taught poorly is worth less than nothing This course 7 will introduce you to the basic methods of statistical inference and prediction but will not be a toolbox course 7 will stress the philosophy of statistical analysis the kinds of questions that can be asked the ways in which questions are translated into statistical hypotheses the kinds of procedures that can be used to test those hypotheses the kinds of assumptions that need to be made to test them alternatives to testing hypotheses


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