ABI OMICSS Guide 2021
  • Welcome
  • Week 1
    • Molecular Biology
      • Introduction to Biology
      • Macromolecules
      • DNA & RNA
      • Cell Division
    • Command-Line
      • Connecting to the Server
      • The Linux Command-Line For Beginners
      • The Bash Terminal
    • R Programming
      • Getting Started
      • The Basics
      • Data Types
    • Week 1 Exam
  • Week 2
    • Molecular Biology
      • DNA Proofreading And Repair
      • Telomeres and Telomerase
      • Genes
      • The One Gene, One Enzyme Hypothesis
      • Transcription
      • Translation
    • R Programming
      • Data Types (continuation)
      • Reading Data
      • Subsetting
      • Control Structures
      • Functions
      • Scoping Rules
    • Week 2 Exam
  • Week 3
    • Molecular Biology
      • tRNA and Ribosomes
      • Stages of Translation & Protein Targeting
      • Heredity
      • Probabilities In Genetics
    • R Programming
      • Loop Functions
      • Base Graphics
    • Statistics and R
      • The Basics
    • Week 3 Exam
  • Week 4
    • Molecular Biology
      • Interesting Cases of Genes
      • The Chromosomal Basis of Inheritance
      • Variation in Species
      • Phenotype plasticity
    • R Programming
      • Practice 2
      • Practice 3
    • Statistics and R
      • Random Variables and Probability Distributions
      • Central Limit Theorem
    • Week 4 Exam
  • Week 5
    • Statistics and R
      • Confidence Interval
      • Introduction to Inference
      • t-distribution and Comparing Means
      • Linear Models
    • Experimental Techniques
      • Polymerase Chain Reaction (PCR)
      • Gel Electrophoresis
      • Sanger Sequencing
      • NGS Sequencing
    • Week 5 Exam
  • Week 6
    • Statistics and R
      • Power
      • ANOVA
      • Covariance and Correlation
    • NGS
      • Basic Unix Commands
      • Sequences and Genomic Features
      • FastQC
      • Practice Exercises
    • Week 6 Exam
  • Week 7
    • Statistics and R
      • Monte Carlo Simulation
      • Exploratory Data Analysis
      • Linear Regression
    • NGS
      • BEDtools
      • Alignment and Sequence Variation
      • Integrated Genomics Viewer
    • Week 7 Exam
  • Week 8
    • NGS
      • Variant Calling With GATK
      • Practice 1
    • Week 8 Exam
  • Module Syllabi
  • Additional Resources
  • Conclusion
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  1. Week 7
  2. Statistics and R

Exploratory Data Analysis

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Last updated 3 years ago

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In statistics, exploratory data analysis is an approach to analyzing data sets to summarize their main characteristics, often using statistical graphics and other data visualization methods.

To learn more about exploratory data analysis, review the following content from the , and return here afterward:

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Scatterplot
Scatterplot Exercises
Symmetry of Log Ratios
Symmetry of Log Ratios Exercises
Plots to Avoid
Avoid Pseudo 3D
Plots to Avoid Exercises