Observational error

Formal sciences
Statistics
Statistical inference
Sensitivity analysis

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Related lectures (32)

Hypothesis Testing & Confidence Intervals

Covers hypothesis testing, power, confidence intervals, and small sample considerations.

Bayesian Inference: Error Minimization

Discusses error minimization in Bayesian inference and the importance of prior knowledge in the inference process.

Error Correction: Shor Code

Covers error correction using Shor codes for protection against bit-flip and phase-flip errors.

Calibration analysis of flow meters

Covers the analysis of calibrations for flow meters and parameters like atmospheric temperature, pressure, humidity, and timing.

Provable Benefits of Overparameterization in Model Compression

Explores the provable benefits of overparameterization in model compression, emphasizing the efficiency of deep neural networks and the importance of retraining for improved performance.

Testing: Specification Testing

Covers classical hypothesis testing, specification testing, and errors in hypothesis testing in choice models.

Specification Testing

Covers specification testing in choice models, highlighting the impact of errors.

Autocorrelation and Instrumental Variables

Explores autocorrelation, instrumental variables, and challenges in regression analysis.

Convolutional Networks: Motivation & Ideas

Explores the motivation and ideas behind convolutional networks, emphasizing weight sharing and pooling layers.

Scala Lens Compilation

Covers the compilation process of Scala Lens and the use of iterable collections for padding results.

Detecting and Correcting Parameter Errors in Power Grids

Explores methods for detecting and correcting parameter errors in power grids using statistical analysis and computational tools.

Programming Basics: VIAY Interface and File Handling

Explores VIAY interface, file handling, debugging, and multithreading in LabVIEW programming.

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