Handout 01
Date: 2022-09-15
Topic: Introduction Data Analytics with R and Rstudio

Literature
Handout
Ismay & Kim (2022) Preface and Chapter 1

Basics for Data Analytics

  • Purpose Data Analytics: Transform Data into Information
  • Structured and Unstructured Data
    • Focus this course: Structured Data
  • Types of Data
    • Categorical (Qualitative)
      • Nominal
      • Ordinal
    • Numeric (Quantitative)
      • Interval Scale
      • Ratio Scale
  • Collecting Data
    • Primary Data
    • Secondary Data
      • Data File Formats
      • Joining Data Files
  • Cleaning Data
    • Data Matrix
    • Examining Outliers
    • Handling Missing Values
    • Adjusting Formats
      • decimal separator
      • thousands separator
      • ‘scientific notation’
      • date format
  • EDA: Exploratory Data Analysis
    • Visualisations: Graphing Data
    • Summary Statistics
      • Centre
      • Variation or Spread
      • (Skewness)
    • SOCS: Shape, Outliers, Centre, Spread
  • Software
    • Spreadsheet
      • MS Excel; Numbers (Apple); Google Sheets; …
    • Commercial Packages
      • SPSS; Minitab; SAS; Stata; …
    • Open Source
      • Jasp; Python; R; …

Introduction R

See: Ismay & Kim (2022) Chapter 1