KRIGOLSON TEACHING
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Right or Wrong

Given the new version of our experiment, it is possible that people can make mistakes. For example, some people might push "a" for a right square or "a" for a central square. Indeed, in a lot of experimental paradigms determining right or wrong is of equal if not more interest than reaction time or another variable.

​The logic we will use here is simple. Let's think it through. We know what the stimulus location is. Indeed, in our previous code we have the variable stimulus_side which is assigned to be 1 for a left stimulus, 2 for a right stimulus, and 0 for a central stimulus. And, we also know what the block_type is - 1 for simple reaction time (i.e., a central stimulus) and 2 for choice reaction time (i.e., a left or right stimulus). Thus, if block_type == 1 and stimulus_type == 0 then we know that the correct response has to be 
the space bar. So, we can create a new variable response_type and assign it a 0 if the space bar is pressed, a 1 if the "a" key is pressed, and a 2 if the "l" key is pressed.

To implement this to evaluate what is happening we need to change two things. 

​First, when someone presses a response we need to not just compute reaction time, we also need to assign a response_type. This is easy, we can tweak the code to not care about block_type when someone responds and just assign a reaction time value and a value to response_type as outlined above.

Second, we need to evaluate whether someone is right or wrong using some if statements like this:

response_correct = 0;

if block_type == 1 & stimulus_side == 0 & response_type == 0
     response_correct = 1;
end

You will note I made a default assumption that people were wrong. This makes life a whole lot easier as we will not need if statements for all possible combinations, just when they are correct and all three of our if criteria are met.

I have implemented this code HERE. Take a look, then move onto the Things To Do. You will note that any response key is valid in any block, not just the block where the different responses are appropriate.

Things To Do
1. Use your MATLAB skills to see if you can generate some results from this data. For example, mean response time and mean accuracy.
2. Use a strategy similar to that for the way we specified blocks here to specify trials to guarantee there is an equivalent number of left and right trials in each block. You will have to change the number_of_trials to 6 of course but you will need to specify in advance a trial type and then shuffle it each block.
3. Change the number of responses needed by adding a third block_type where the square can be in any one of three positions (left, middle, right).

  • 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 >
      • LABORATORY
      • PRACTICUM
    • EPHE 357
  • STATISTICS
    • LECTURE >
      • INTRODUCTION TO R
      • DESCRIPTIVE STATISTICS
      • VISUALIZING DATA
      • Correlation and Regression
      • MULTIPLE REGRESSION
      • LOGIC OF NHST
      • T TESTS
      • ANOVA
      • POST HOC ANALYSIS
      • NON PARAMETRIC STATISTICS
      • FACTORIAL ANOVA
      • Repeated Measures ANOVA
      • Mixed ANOVA
      • MULTIVARIATE ANOVA
      • THE NEW STATISTICS
      • Bayesian Methods
    • ASSIGNMENTS >
      • Introduction to R >
        • INTRODUCTION TO R
        • LOADING DATA
        • DATA TABLES
      • Descriptive Statistics >
        • Mean, Median, and Mode
        • VARIANCE
        • CONFIDENCE INTERVALS
        • SHORTCUTS
      • Visualizing Data >
        • PLOTTING BASICS
        • BAR GRAPHS
        • BOXPLOTS
        • HISTOGRAMS
        • USING GGPLOT I
        • USING GGPLOT II
        • USING GGPLOT III
      • Correlation and Regression >
        • CORRELATION
        • REGRESSION
      • MULTIPLE REGRESSION >
        • MULTIPLE REGRESSION
      • Logic of NHST >
        • Sample Size and Variance
        • DISTRIBUTIONS
        • TESTING DISTRIBUTIONS
      • T-Tests >
        • Single Sample TTests
        • Paired Sample TTests
        • Independent Sample TTests
      • ANOVA >
        • ANOVA ASSUMPTIONS
        • ANOVA
      • POST HOC ANALYSIS >
        • POSTHOC ANALYSIS
      • NON PARAMETRIC STATISTICS >
        • WILCOXON TEST
        • WILCOXON SIGNED TEST
        • MULTIPLE GROUPS
      • FACTORIAL ANOVA
      • REPEATED MEASURES ANOVA >
        • RM ANOVA
        • TREND ANALYSIS
      • MIXED ANOVA
      • MULTIVARIATE ANOVA
      • THE NEW STATISTICS
      • BAYESIAN TTESTS
    • RESOURCES
    • R TIPS
  • 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
  • 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
  • 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