29 Statistical Concepts Explained in Simple English – Part 12

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This resource is part of a series on specific subjects related to information science: regression, clustering, neural networks, deep learning, decision trees, ensembles, correlation, Python, R, Tensorflow, SVM, data reduction, function selection, speculative design, cross-validation, model fitting, and lots of more. Part 11

29 Statistical Concepts Explained in Simple English

  • Negative Binomial Experiment / Distribution: Definition, Examples
  • Nested Model, ANOVA and Factors: Simple Definitions and Examples
  • Nominal Ordinal Interval Ratio: Examples
  • Nominal Variable: Definition and Examples
  • Differential & Non-Differential Misclassification
  • Nonlinear Regression: Simple Definition & Examples
  • Non-Probability Sampling: Definition, Types
  • Non Response Bias: Definition, Examples
  • Normalized Data / Normalization
  • Normal Probability Plot: Definition, Examples
  • Normal Probability Practice Problems and Answers
  • Nuisance Variable & Nuisance Parameter: Definition, Examples
  • Number Needed to Harm NNH: Definition
  • Observation in Statistics: Simple Definition & Examples
  • Observer Bias / Research or Experimenter Bias: Definition, Examples…
  • Odds Ratio Calculation and Interpretation
  • Ogive Graph / Cumulative Frequency Polygon in Easy Steps
  • Omega Squared: Definition
  • One Sample T Test: How to Run It, Step by Step
  • One Sample Z Test: How to Run One
  • Open Ended Distribution: Definition and Examples
  • Order Effects: Definition, Examples and Solutions
  • Order of Integration (Time Series): Simple Definition / Overview
  • Order Statistics: Simple Definition, Examples
  • Ordinal Numbers, Variables and Data: Definition and Examples
  • Pairwise Independent, Mutually Independent: Definition, Example
  • Parallel Design / Parallel Group Study
  • Parallel Forms Reliability (Equivalent Forms)
  • Non Parametric Data and Tests (Distribution Free Tests)

Previous editions, in alphabetical order, can be accessed here:

 Part 1 | Part 2 | Part 3 | Part 4 | Part 5 | Part 6 | Part 7 | Part 8 | Part 9 | Part 10 | Part 11

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