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WILCOXON SIGNED RANK TEST

The Wilcoxon Signed Rank test is the non-parametric equivalent of a dependent samples t-test. Note, the name is very close to its independent samples equivalent. For example, if you have dependent measurements (day one versus day two) and you have concerns about the normality of the difference scores it would be appropriate to use a Wilcoxon Signed Rank test.

​Load the data HERE into R into a table called data. Column 1 is participant numbers, column 2 is a grouping variable, and column 3 is the dependent measure. Note that the participant numbers repeat themselves indicating a repeated or dependent measurement.

data = read.table("ttestdata2.txt")


To assess the normality of the difference scores, you could do a couple of different things. One might be:

data1 = data$V3[data$V2==1]
data2 = data$V3[data$V2==2]
differences = data2-data1
hist(differences)


The resulting histogram looks normal, so you could use a dependent samples ttest:

​
t.test(data$V3~factor(data$V2),paired=TRUE)

But, if you were concerned about a violation of the assumption you could use the Wilcoxon Signed Rank test:


wilcox.test(data$V3~factor(data$V2),paired=TRUE)

As with the test in the previous assignment, this test returns a p value and a test statistics, in this instance V. Sorry to be confusing, but V actually reflects T - a difference in the positive and negative ranked values (see Field).
  • NEUROSCIENCE
    • NEUROSCIENCE 100 >
      • NEURO 100 INTRODUCTION
      • NEURO 101 ADVANCED
      • NEURO 102 AGING
      • NEURO 103 MEMORY
      • NEURO 104 DECISION MAKING
      • NEURO 105 LEARNING
      • Research Statistics
    • NRSC 500B / MEDS 470
  • Kinesiology
    • EPHE 245
    • EPHE 357
  • STATISTICS
    • BIOMEDICAL STATISTICS
    • MULTIVARIATE STATISTICS >
      • MULTIPLE REGRESSION
    • RESOURCES
    • R TIPS
  • MATLAB
    • THE BASICS >
      • Hello World
      • BASIC MATHEMATICS
      • VARIABLES
      • Matrices
      • Writing Scripts
      • PATHS AND DIRECTORIES
      • USER INPUT
      • FOR LOOPS
      • WHILE LOOPS
      • IF STATEMENTS
      • RANDOM NUMBERS
    • STATISTICS >
      • LOADING DATA
      • DESCRIPTIVE STATISTICS
      • MAKING FUNCTIONS
      • BAR GRAPHS
      • LINE GRAPHS
      • TTESTS
    • EXPERIMENTS: THE BASICS >
      • DRAWING A CIRCLE
      • DRAWING MULTIPLE OBJECTS
      • DRAWING TEXT
      • DRAWING AN IMAGE
      • PLAYING A TONE
      • KEYBOARD INPUT
      • BUILDING A TRIAL
      • BUILDING TRIALS
      • NESTED LOOPS
      • RIGHT OR WRONG
      • SAVING DATA
    • EXPERIMENTS: ADVANCED >
      • STROOP
      • N BACK
      • Oddball
      • Animation
      • VIDEO
    • EEG and ERP Analysis >
      • ERP Analysis
      • FFT Analysis
      • Wavelet Analysis
  • Directed Studies
    • Advanced Topics in Motor Control A
    • Advanced Topics in Motor Control B
    • An Introduction to EEG
    • Advanced EEG and ERP Methods
    • Neural Correlates of Human Reward Processing
    • Independent Research Project
  • RESOURCES
    • EXCEL
    • HOW TO READ A RESEARCH PAPER
    • HOW TO WRITE A RESEARCH PAPER
  • Workshops
    • Iowa State EEG Workshop 2018
  • Python
    • The Basics >
      • Setting Up Python
      • Hello, world!
      • Basic Math & Using Import
      • Variables
      • Matrices
      • Scripts
      • User Input
      • For Loops