Statistical Concepts: Difference between revisions

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** Dependent variable (criterion)
** Dependent variable (criterion)
** Independent variable (predictor)
** Independent variable (predictor)
* [[Classification]]


* [[Bayes Rule]]
* [[Bayes Rule]]

Revision as of 20:18, 18 December 2017

Internal

Concepts

  • Mean/Median/Mode. Difference between mean and average.
  • Unique Median
  • standard deviation
  • Regression and Linear Regression.
    • Dependent variable (criterion)
    • Independent variable (predictor)
  • Bayes Rule
  • Scatter Plot
  • Linearity (linear exact or not exact)
  • Positive and negative linear relationship.
  • Outlier
  • Deviation
  • Noise - deviation from a linear graph.
  • Monotonicity.
  • Bar Charts. Applies to 2D data.
  • Global trends.
  • Historgram. A bar chart where the vertical axis is a frequency count, as a function of the range. Applies to 1D data.
  • Frequency Count
  • Pie charts - represent relative outcomes.
  • Unrelated data
  • Simpson's paradox
  • Be skeptical and really understand how to turn raw data into conclusions.
  • Probability - the opposite of statistics.
  • P() notation
  • Truth table
  • Probability of a composite event (independence)
  • Dependence
  • Conditional probability
  • Conditional probability notation - important for Bayes Rule
  • Total probability
  • Bayes Rule
    • Prior probability
    • Unreliable measurement (Sensitivity/Specificity)
    • Joint probabilty
    • Posterior probabilty
  • Probability Distribution
  • Continous Probability Distribution.
  • Density of probability
  • Estimators
  • Laplacian estimator
  • Empirical (observational) frequency
  • Maximum likelihood estimator
  • Dirichelet data
  • Laplacian Estimator
  • Mode, bimodal, multimodal
  • Variance
  • Standard Deviation
  • Standard Score
  • 95% percentile.

Correlation and Causation

TODO