SEX SELLS, SEX CELLS & 2 BODY PROBLEMS BEFORE YOU GET THE WHOLE TRUTH YOU HAVE TO GET THE HALF TRUTH Uneven distributions of wealth & abundance: Is the.

Slides:



Advertisements
Similar presentations
Original Figures for "Molecular Classification of Cancer: Class Discovery and Class Prediction by Gene Expression Monitoring"
Advertisements

Statistics 100 Lecture Set 7. Chapters 13 and 14 in this lecture set Please read these, you are responsible for all material Will be doing chapters
Evolution of Biodiversity
Sampling Distributions (§ )
Analysis. Start with describing the features you see in the data.
Chapter 13 Key Issue #1.
Spreadsheets in Finance and Forecasting Introduction to Charts, Summary Values and Pivot Tables.
Sampling Distribution of & the Central Limit Theorem.
Statistics for the Social Sciences
Lecture 2 PY 427 Statistics 1 Fall 2006 Kin Ching Kong, Ph.D
Properties of Community Data in Ecology Adapted from Ecological Statistical Workshop, FLC, Daniel Laughlin.
Equitability and dominance in online forums: an ecological approach Jon Rosewell EATING, 13 th November 2008 Dept of Communications and Systems Faculty.
Transforms What does the word transform mean?. Transforms What does the word transform mean? –Changing something into another thing.
Copyright (c) Bani Mallick1 Lecture 4 Stat 651. Copyright (c) Bani Mallick2 Topics in Lecture #4 Probability The bell-shaped (normal) curve Normal probability.
Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc. Chap 6-1 Chapter 6 The Normal Distribution and Other Continuous Distributions.
9/17/071 Community Properties Reading assignment: Chapter 9 in GSF.
BPS - 5th Ed. Chapter 31 The Normal Distributions.
Crosstabs. When to Use Crosstabs as a Bivariate Data Analysis Technique For examining the relationship of two CATEGORIC variables  For example, do men.
Statistical Thinking Space Shuttle O-ring Failure The night before the disaster, it was predicted that it would be a cold night (30°F). Some NASA engineers.
1 FRACTIONS, DECIMALS, AND PERCENTS Week 4. Helen Holt2 Session Outcomes: Be able to read, write, order and compare common fractions. To identify equivalences.
Community Attributes Kenneth M. Klemow, Ph.D. Wilkes University Kenneth M. Klemow, Ph.D. Wilkes University.
Math 116 Chapter 12.
Species Richness, Simpson’s, and Shannon-Weaver…oh my…
Density Curves Normal Distribution Area under the curve.
Agronomic Spatial Variability and Resolution What is it? How do we describe it? What does it imply for precision management?
PSYCHOLOGY: Themes and Variations Weiten and McCann Appendix B : Statistical Methods Copyright © 2007 by Nelson, a division of Thomson Canada Limited.
Sample size vs. Error A tutorial By Bill Thomas, Colby-Sawyer College.
MANAGEMENT AND ANALYSIS OF WILDLIFE BIOLOGY DATA Bret A. Collier 1 and T. Wayne Schwertner 2 1 Institute of Renewable Natural Resources, Texas A&M University,
Agronomic Spatial Variability and Resolution What is it? How do we describe it? What does it imply for precision management?
Statistics in Applied Science and Technology Chapter 13, Correlation and Regression Part I, Correlation (Measure of Association)
The Scientific Method. Steps of Scientific Method 1.Observation: notice and describe events or processes 2.Make a question 1.Relate to observation 2.Should.
Chapter 10 The Geography of Diversity
TYPES OF STATISTICAL METHODS USED IN PSYCHOLOGY Statistics.
MGS3100_04.ppt/Sep 29, 2015/Page 1 Georgia State University - Confidential MGS 3100 Business Analysis Regression Sep 29 and 30, 2015.
1 Lecture 1 Density curves and the CLT Quantitative Methods Module I Gwilym Pryce
Review of the Basic Logic of NHST Significance tests are used to accept or reject the null hypothesis. This is done by studying the sampling distribution.
Macroecology & uneven distributions of wealth Ken Locey.
11/23/2015Slide 1 Using a combination of tables and plots from SPSS plus spreadsheets from Excel, we will show the linkage between correlation and linear.
Bivariate Data Analysis Bivariate Data analysis 4.
Sociology 5811: Lecture 3: Measures of Central Tendency and Dispersion Copyright © 2005 by Evan Schofer Do not copy or distribute without permission.
Last Time Normal Distribution –Density Curve (Mound Shaped) –Family Indexed by mean and s. d. –Fit to data, using sample mean and s.d. Computation of Normal.
Macroecology & uneven distributions of wealth Ken Locey.
Biodiversity. Average Size Measure all trees in a transect or quadrat. Produce a size-frequency histogram to show the size distribution. Can also calculate.
Copyright © 2014 by Nelson Education Limited Chapter 11 Introduction to Bivariate Association and Measures of Association for Variables Measured.
26134 Business Statistics Week 4 Tutorial Simple Linear Regression Key concepts in this tutorial are listed below 1. Detecting.
Chapter 8: Probability: The Mathematics of Chance Probability Models and Rules 1 Probability Theory  The mathematical description of randomness.  Companies.
The Normal Approximation for Data. History The normal curve was discovered by Abraham de Moivre around Around 1870, the Belgian mathematician Adolph.
Graphs & Charts: The Art of Data Visualisation Alasdair Rutherford SSPC9C6University of StirlingSpring 2016.
CHAPTER 11 Mean and Standard Deviation. BOX AND WHISKER PLOTS  Worksheet on Interpreting and making a box and whisker plot in the calculator.
4/1/16Oregon State University PH 213, Class #31 Force Fields “Action at a distance” (across “empty” space)—how is this possible? This happens with gravitational.
Scatterplots & Correlations Chapter 4. What we are going to cover Explanatory (Independent) and Response (Dependent) variables Displaying relationships.
Making Sense of Statistics: A Conceptual Overview Sixth Edition PowerPoints by Pamela Pitman Brown, PhD, CPG Fred Pyrczak Pyrczak Publishing.
Week 2 Normal Distributions, Scatter Plots, Regression and Random.
The Statistical Imagination Chapter 7. Using Probability Theory to Produce Sampling Distributions.
The Complex Number System. 1. Write each expression as a pure imaginary number. (similar to p.537 #26)
Analysis of AP Exam Scores
Linear Algebra Review.
Chapter 25 Comparing Counts.
10: Leisure at an International Scale: Sport
Looking at Data - Relationships Data analysis for two-way tables
Week 5 Lecture 2 Chapter 8. Regression Wisdom.
Social Science Statistics Module I Gwilym Pryce
The normal distribution
Descriptive Intervals
Common Core Math I Unit 2: One-Variable Statistics Boxplots, Interquartile Range, and Outliers; Choosing Appropriate Measures.
Common Core Math I Unit 1: One-Variable Statistics Boxplots, Interquartile Range, and Outliers; Choosing Appropriate Measures.
Chapter 26 Comparing Counts.
Sampling Distributions (§ )
MGS 3100 Business Analysis Regression Feb 18, 2016
Presentation transcript:

SEX SELLS, SEX CELLS & 2 BODY PROBLEMS BEFORE YOU GET THE WHOLE TRUTH YOU HAVE TO GET THE HALF TRUTH Uneven distributions of wealth & abundance: Is the world unfair in the same way everywhere all the time? Was Zeno of Elea incontinent? Tips for dancing your PhD: #1. OWN THAT SH*T Art class for Scientists? Inaugural Issue Relativized rank

The uneven nurture of nature Ken Locey For Gavin Inaugural Article (self-reviewed and self-referential)

D istributions of wealth and abundance (DOWs; below) are super important to everything, everywhere, all the time. They reveal the disparity between the haves and the have nots, which is the statistical signature that someone or some thing is getting the short end of the stick. Increasingly uneven DOWs are telltale signs of impending economic instability. In ecology, predicting the shape of the DOW is the first sign that a theory of biodiversity might not be total codswallopy baloney. “Supreme importance attaches to one economic problem, that of the distribution of wealth. Is there a natural law according to which the income of society is divided? If so, what is the law?” – John Bates Clark (1899) Relativized rank

Methods: If you think I developed Python scripts just for this, you’re crazy. Anyway, I used some not so highfalutin coding to select random samples of approximately lots of DOWs from microbial, macrobial, and social/economic datasets (includes DOWs from sports, governments, stocks, and the distribution of supply, use, waste, and production of various resources and commodities)…I then decided to go WAY overboard in tangentially replying to a string of ‘tweets’ led by Gavin Simpson. Specifically, in making this document. Results: Below are plots of kernel density curves, which are sort of like smoothed out histograms but not really, for Smith and Wilson’s evenness index, Simpson’s Diversity and Evenness indices, and the Berger-Parker index which is just the relative abundance or wealth of the most abundant species, the wealthiest country, etc. In terms of evenness, microbial DOWs seem more like economic ones than they do macrobial DOWs. The ones on the right darn near completely overlap, so…

Results cont’d: Below are scatter plots where each dot represents the value of evenness, diversity, or dominance for a single DOW. Microbial and macrobial data seem to follow a more distinct relationship to total abundance N (the sum of all elements in a single DOW) than the socioeconomic datasets. Regardless, bigger N leads to lower evenness…except for the vertical column of economic data points at around N = Look, it’s raining data Relationships of the Berger-Parker index (relative abundance or wealth of the most abundant or wealthy group) and Simpson’s diversity to total abundance are incredibly strong in their amorphous stippled pattern.

Results continued: Here, the left plot looks like hocus-pocus. But it’s also ranging across 10 orders of magnitude in log-log space. So yeah, okay, it is hocus pocus. Apparently, the wealth or abundance of the most wealthy or abundant thing scales strongly and linearly with a 1-to-1 relationship to total abundance or wealth. I mean, really? This is pretty ridiculous. The relationship to richness for microbes and macrobes looks sort of compelling, which makes sense because the number of species generally increases with the number of individuals (e.g. collector’s curves). Of course, the social and economic data have to be all complex and dramatic, and just ruin the whole thing. C onclusion (tentative): 1.) Accounting for total wealth or abundance (N) explains the apparent greater similarities in evenness between microbes and non-ecological distributions of wealth than between microbes and macrobes, i.e., greater N leads to lesser evenness. Microbes and macrobes fill out a pattern that social/economic distributions more greatly vary from, 2.) Apparent similarities in dominance are due to a strong linear relationship of the most abundant rank to N. There are no striking differences between these disparate data compilations. 3.) It is risky to make a statement about patterns of abundance and diversity without accounting for N. There are 19 more orders of magnitude in N to consider!

Ecologist—It’s your lucky week and the year of the horse. Invert your chi and express your inner social butterfly-horse…Pegasus? Physicist—Feeling lonely? Gravity weighing you down? Does the universe feel like it’s full of dark matter? Well, you’re close. Sorry. Mathematician—Solitary numbers, lonely runner conjectures, incompleteness theorems? Your heart chakra is brown noise. Computer Scientist—Need a challenge? Try simulating artificial willful ignorance. Psychologist—pass. Climate scientist—Folks are starting to notice you. I predict this next week will be warmer than usual, so tonight, wear something sexy. Statistician—You’ll never be more likely to be as likely of being more likely as you are right now (p < 0.01). Take the bull by the horns. Philosopher—Relax, the work week is nearly half over. All you have to do, to finish out the other half, is to finish out half of that, and then half of that…crap. Numerologist—The moon’s waning crescent reveals a dwindling chance of winning the lotto. Play before the new moon. Your lucky number is 23 or any set of numbers that multiply, add, subtract, or divide to yield 23.