Robust Summaries & Rank tests

Lucas Schiffer
March 07, 2016

Data Analysis for the Life Sciences

Topics

  • Introduction
  • Median
  • Median Absolute Deviation
  • Spearman Correlation
  • Symmetry of Log Ratios
  • Wilcoxon Rank Sum Test

Introduction


Thermal Cycler https://tinyurl.com/z5meacs


Flow Cytometer https://tinyurl.com/zfgun7w


Liquid Scintillation Counter https://tinyurl.com/jerufaq


FTIR Spectrometer https://tinyurl.com/hdrzs6x

Introduction

plot of chunk unnamed-chunk-2

Mean =  1.11 
SD = 10.03 
Median = 0.17
  • Expensive Devices Make Mistakes
  • Expert Researchers Make Mistakes
  • Systematic Errors Occur Often
  • Random Errors Occur Often
  • Equipment Cost ≠ Error Rate

Median

  • Robust to Outliers
  • For Ordered Data, Given by the Middle Term
  • Must Average Two Terms Where n of Terms is Even
  • The Smallest Value of i that Satisfies the Inequality

\[ \sum_{i=1}^{j} f_i ≥ \frac{n+1}{2} \]

Median

plot of chunk unnamed-chunk-3

Mean =  1.11 
SD = 10.03 
Median = 0.17

plot of chunk unnamed-chunk-4

Mean =  0.11 
SD = 0.9 
Median = 0.11

Median Absolute Deviation

  • Robust version of standard deviation
  • Compute the Difference Between Each Point and the Median
  • Then Take the Median of Their Absolute Values

\[ \operatorname{MAD} = \operatorname{median}_{i}\left(\ \left| X_{i} - \operatorname{median}_{j} (X_{j}) \right|\ \right), \ \]

Median Absolute Deviation

plot of chunk unnamed-chunk-5

SD = 10.03

plot of chunk unnamed-chunk-6

MAD = 0.89

Spearman Correlation

  • Also Known as Spearman's Rho
  • Raw Values Are Standardized and Ranked
  • Ranked Values Range from 0 to 1
  • Robust Because Outliers Rank Lower

\[ r_s = \rho_{\operatorname{rg}_X,\operatorname{rg}_Y} = \frac {\operatorname{cov}(\operatorname{rg}_X,\operatorname{rg}_Y)} { \sigma_{\operatorname{rg}_X} \sigma_{\operatorname{rg}_Y} } \]

Spearman Correlation

plot of chunk unnamed-chunk-7

plot of chunk unnamed-chunk-8

Symmetry of Log Ratios

  • Properties of Logarithms Yields Symetric Ratios
  • Allows for Normalization of Exponential Data
  • Data Becomes Linear, More Amenable to Analysis
  • Robust Statistics for Exponential Data

\[ \log(x/y)=\log(x)-\log(y)=-(\log(y)-\log(x))=\log(y/x) \]

Symmetry of Log Ratios

plot of chunk unnamed-chunk-9

plot of chunk unnamed-chunk-10

Symmetry of Log Ratios

plot of chunk unnamed-chunk-11

plot of chunk unnamed-chunk-12

Wilcoxon Rank Sum Test

  • Also Known as the Mann-Whitney Test
  • Just as Mean and Standard Deviation are Suseptible to Outliers, so too is the T-Test
  • In Essence Data are Combined, Ranked, Stratified into Groups, and Finally Given an Average Rank
  • Provides a Non-Parametric Method for Hypothesis Testing

Wilcoxon Rank Sum Test

plot of chunk unnamed-chunk-13

t-test pval: 0.04439948

plot of chunk unnamed-chunk-14

Wilcox test pval: 0.1310212

The End

The Exercises <- http://rpubs.com/schifferl/rse