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.

**23 Statistical Concepts Explained in Simple English**

- Face Validity: Definition and Examples
- Factor analysis: Easy Definition
- False Discovery Rate: Simple Definition, Adjusting for FDR
- False Positive and False Negative: Definition and Examples
- Familywise Error Rate (Alpha Inflation): Definition
- Fat Tail Distribution: Definition, Examples
- 5 Number Summary in Excel: Easy Steps with Video
- Outliers: Finding Them in Data, Formula, Examples. Easy Steps and V...
- How to Find Pearson's Coefficient of Skewness in Excel
- Pooled Sample Standard Error: How to Calculate it
- Regression Slope Intercept: How to Find it in Easy Steps
- Standard Error Excel 2013 in Easy Steps
- Standard Error of Regression Slope
- How to Find t Critical Value on TI 83
- Variance in Minitab: How to Find it
- Finite Population Correction Factor FPC: Formula, Examples
- Fisher Z-Transformation
- Fleiss' Kappa
- Fmax / Hartley's Test: Definition, Step by Step Example, Table
- Fractile Definition Usage and How to Calculate
- Frequency Distribution Table in Excel -- Easy Steps!
- Frequency Polygon: Definition and How to Make One
- Friedman's Test / Two Way Analysis of Variance by Ranks

Previous editions can be accessed here: Part 1 | Part 2 | Part 3 | Part 4 | Part 5 | Part 6.

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