# 21 Statistical Concepts Explained in Simple English – Part 4

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.