Author: Vincent Granville
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.
27 Statistical Concepts Explained in Simple English
- Cumulative Frequency Distribution: Simple Definition, Easy Steps
- Cumulative Frequency Table in Excel: Easy Steps
- Data Collection Methods
- What is a Decile?
- Decision Tree: Definition and Examples
- Degrees of Freedom: What are they?
- Density Curve Examples
- Dependent Variable: Definition and Examples
- Design Effect: Definition, Examples
- Deterministic: Definition and Examples
- Detrend Data
- Dichotomous Variable: Definition
- Difference Between BinomPDF and BinomCDF
- Curse of Dimensionality & High Dimensional Data
- Acyclic Graph & Directed Acyclic Graph: Definition, Examples
- Direction of Association in Statistics: What is it?
- Discrete Probability Distribution: Definition & Examples
- What is a Discrete Variable in Statistics?
- Discrete vs Continuous variables: How to Tell the Difference
- Disjoint Events: Definition, Examples
- Dispersion / Measures of Dispersion: Definition
- Dixon’s Q Test: Definition, Step by Step Examples + Q Critical Values Tables
- Double Sampling: Simple Definition, Types
- Dummy Variables / Indicator Variable: Simple Definition, Examples
- Duncan’s Multiple Range Test (MRT)
- Dunnett’s Test / Dunnett’s Method: Definition
- Dunn’s test: Definition
Previous editions can be accessed here: Part 1 | Part 2 | Part 3 | Part 4. 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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