21 Statistical Concepts Explained in Simple English – Part 4

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This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, decision trees, ensembles, correlation, Python, R, Tensorflow, SVM, data reduction, feature selection, experimental design, cross-validation, model fitting, and many more. To keep receiving these articles, sign up on DSC. 

21 Statistical Concepts Explained in Simple English

  • Content Validity (Logical or Rational Validity)
  • Contingency Coefficient: Definition
  • Continuous Probability Distribution
  • Continuous Variable Definition (Continuous Data)
  • Contour Plots: Definition, Examples
  • Control Group: Definition, Examples and Types
  • Control Variable: Simple Definition
  • Convenience Sampling (Accidental Sampling): Definition, Examples
  • Convergent Validity and Discriminant Validity: Definition, Examples
  • Cook’s Distance / Cook’s D: Definition, Interpretation
  • Correlation Matrix: Definition
  • Counterbalancing in Research
  • Covariance in Statistics: What is it? Example
  • Covariate Definition in Statistics
  • Cramer-Rao Lower Bound
  • Criterion Validity: Definition, Types of Validity
  • Criterion Variable: Definition, Use and Examples
  • Critical Z Value TI 83: Easy Steps for the InvNorm Function
  • Cronbach’s Alpha: Simple Definition, Use and Interpretation
  • C-Statistic: Definition, Examples, Weighting and Significance
  • Cumulative Distribution Function CDF

Previous editions can be accessed here: Part 1 | Part 2 | Part 3. Also, if you downloaded our book Applied Stochastic Processes, there is an error page 64, that I fixed. The new version of the book can be found here. 

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