• 1.An introduction to the dataset and the significance of outlier analysis.
    • 1.What data is involved
    • 2.Variable type and brief description
      • class: 0 = No chronic kidney disease, 1 = Have
      • age: Patient age
      • glu: Glucose levels in the blood
      • sod: Sodium levels in the blood
      • pot: Potassium levels in the blood
  • 2.Variable type and brief description

    • 1.IQR

      • IQR specific steps
      • Values outside this range are considered outliers.

      image.png

      • Implementation steps of the two methods

      image.png

    • 2.Boxplot Visualization:Display outliers for each variable.

  • 3.Visualizations illustrating the presence of outliers.
    • 1.Zhang
      • dlookr: Tools for data cleaning, transformation, analysis, and visualization
    • 2.Teng
      • A box plot is used to show the outliers of each variable, and a scatter plot is used to visually show the location of the outliers.
  • 4.A discussion on the implications of outliers and your decision regarding their treatment.
    • 1.Zhang
    • 2.Teng
  • 5.A conclusion summarizing your findings.