Data Science Knowledge Skills Ability (KSA)

  • Inferential Statistics and Sampling techniques:
    1. Confidence levels and Intervals
    2. Zee scores and T distribution
    3. Defining Sample Size
    4. Dependent Samples
  • Profiling and group analysis on two and multiple groups:
    1. T-test and Chi-Square Test
    2. R-Anova
    3. Non-Parametric Tests
    4. Regression and Correlation analysis
  • Machine Learning Tools:
    1. Multiple Regression
    2. Discriminant Analysis
    3. Classification trees: CART
    4. Random Forests
    5. Clustering and K-Means technique
    6. Detection of Anomalies and optimization of campaigns
  • Forecasting Methodologies:
    1. Trends and Averaging
    2. Exponential Smoothing
    3. Time Series and Fourier Analysis
    4. ARIMA Models
  • Programming in R:
    1. Transforming and manipulating exploratory data
    2. Mathematical modeling
    3. Statistical modeling