KRIGOLSON TEACHING
  • 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
  • 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

1b. Loading Data

Before we can do any statistics, you need to be able to load your data into R. There are a variety of ways to do this of course, but I will focus on the read.table command. We will work with the file data.txt. I would encourage you to open this file in a text editor or EXCEL to take a look at it. This is the standard way to lay out data for statistical analysis, a column(s) for the independent variable, here coded as a 1 or 2 and column(s) with data, were negative numbers in column 2 ranging from approximately -2 to -12 and positive numbers ranging from 200 to 500 in column 3.

Open R Studio. Using Session --> Set Working Directory --> Choose Directory set the directory to the one in which you have placed the data.txt file. I strongly encourage you to create a R directory somewhere and place all your files there. Note, you will see the command for changing the working directory in your command window after using the Session drop down menu. To do this from the command prompt you would use 
setwd("~/R") where whatever is in quotes is your path to your R directory.

At the command prompt, ">" type the following command: mydata = read.table("data.txt").

You should now see your data in R Studio. You can either use the command 
View(mydata) or click on the Environment tab and look under Data. Then click on mydata to see your data.

We have loaded the data into a structure called a table (hence the command read.table). In R tables are used to hold statistical data. Note that the columns have labels V1, V2, and V3. These are the default column labels in R. To see the first column for instance you would type mydata$V3 at the command prompt (note the $ - this tells R that you want the column V3 in the table mydata). Do this now. You should see the numbers in the third column with numbers in [ ] brackets which provide the index of the first number in the row. For example, the second number in the third column would be identified as mydata$V3[2].

  • 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
  • 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