object | Observations and Variables |

objective function | Optimization - Introduction |

| Optimization - Response Function |

objects | Data Matrices |

observation | Observations and Variables |

one sample chi-square test | One Sample Chi-Square-Test |

one-sample t-test | One-Sample t-Test - Large Samples |

| One-Sample t-Test - Small Samples |

| One-Sample t-Test |

one-sided tests | One-Sided vs. Two-Sided Tests |

optimization | Optimization - Introduction |

| Optimization Methods |

| Optimization Methods - Brute Force Approach |

| Optimization Methods - Genetic Algorithms |

| Optimization Methods - Gradient Descent |

| Optimization Methods - Monte Carlo Simulations |

| Optimization - Response Function |

| Optimization - Visualization of the response function |

| Simplex Algorithm |

order of a matrix | Matrix Algebra - Fundamentals |

ordinal scales | Scales |

orthogonal | Orthogonality |

orthonormal | Orthogonality |

outliers | Scatter, Covariance, and Correlation Matrix |

| Outliers |

| Outlier Tests |

| Outlier Tests - Basic Rules |

| Outlier Test - Dean and Dixon |

| Exercise - Create a Data Set with Outliers |

| Walsh's Outlier Test |

| Grubbs' Outlier Test |

overfitting | Generalization and Overtraining |

overtraining | Generalization and Overtraining |