knowledge-gaps.md

Knowledge Gaps

Statistics

• Standard Error (SE)
  • How to interpret this concept
  • What's the range of SE?
• z-statistic
  • How to interpret this concept
  • What's the range of z-statistic?
• p-value
  • How to interpret this concept: what's the meaning of a low/high p-value
  • What's the range of p-value?
• collinearity
  • How to interpret this concept
• probability density
  • How to interpret this concept
    • it describes how the probability of a random variable is distributed over a range of values
• Degrees of Freedom

Linear Regression

• How a linear regression behaves
  • Illustration of a graph
  • Equation
  • What do we use to estimates the βs?

Classification

• How a logistic regression behaves
  • Illustration of a graph
  • Equation
  • What do we use to estimates the βs?
• How a multiple logistic regression behaves
  • Illustration of a graph
  • Equation
  • What do we use to estimates the βs?
• How the ratio between parameters and samples influence the model fitting?
  • The higher the ratio of parameters p to number of samples n, the more we expect this overfitting to play a role
  • Overfitting: The model can become overly complex, capturing noise in the training data rather than the underlying pattern. This leads to poor generalization to new, unseen data.
• What's covariance matrix?
  • A covariance matrix is a square matrix that contains the covariances between pairs of variables in a dataset.
  • Covariance measures the degree to which two variables change together

Machine Learning

• Theory on Support Vector Machines (Intro to Stats Learning)
• Theory on Decision Tree (Intro to Stats Learning)
• Theory on Random Forest (Intro to Stats Learning)
• Theory on Cross Validation (Intro to Stats Learning)