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      • 3D Object Detection
      • A* Algorithm
      • AB Testing
      • Activation Functions
      • AdaBoost
      • Additive feature attribution methods
      • Adversarial Attacks
      • AI Explainability and GDPR
      • Akamai
      • Algorand
      • All (Probes) Against All (Gallery)
      • Amazon Batch
      • Amazon EC2
      • Amazon ECS
      • Amazon EKS
      • Amazon Elastic Beanstalk
      • Amazon Fargate
      • Amazon Lambda
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      • Anonymity on the Internet
      • ANOVA - Analysis of Variance
      • Anti-Spoofing Evaluation
      • API - Application Programming Interface
      • ASICs
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      • Autoencoders
      • Automata Learning
      • AWS
      • BaaS - Backend as a Service
      • Backpropagation
      • Bag of N-grams
      • Bag of Words (BoW)
      • Bagging
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      • Bayes' Theorem
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      • Bayesian Statistics
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      • Biometric traits requirements
      • Bitcoin
      • Bitcoin Address Generation
      • Böhm Theorem
      • Boosting
      • Box Plots
      • Brave Search vs DuckDuckGo
      • Bubble Sort
      • BYOL
      • CAP Theorem
      • Carbon Offset
      • Case-based vs Instance-based Counterfactual Generation
      • Causal Rule Mining
      • cd command
      • Central Limit Theorem
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      • Chebyshev Distance
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      • Church-Rosser and Combinatory Logic
      • CI-CD
      • Class Components
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      • Contrastive Learning
      • Convolutional Neural Networks
      • Correlation and Causation in Data
      • Correlation coefficient
      • Counterfactual Explanation
      • Counterfactual Explanations in Recommender Systems
      • Covariance
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      • cp command
      • Curry-Howard Isomorphism
      • Curse of dimesionality
      • Dark Web
      • Data in Machine Learning
      • Data Retrieval vs Data Mining
      • Deadlock in Distributed Systems
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      • Decidability value
      • Deep ReLU Networks
      • Deep Representations for Visual Search
      • Descriptive Statistics
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      • Entropy
      • Equivalences in Lambda Calculus
      • Error detection in speech recognition tasks
      • Error Handling in HCI
      • Ethereum
      • Euclidean Distance
      • Examples of Sequence Modelling Problems
      • EXISTS operator in SQL
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      • Google Cloud
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      • Human-Computer Interaction on the Web
      • Hyperbolic Deep Learning
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      • Interquartile Range
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      • Iris Recognition
      • Is it possible to approximate any deep learning opaque model with an automaton?
      • Jaccard Distance
      • Jensen’s inequality
      • K-Fold Cross Validation
      • kNN-graph
      • Kullback-Leibler divergence
      • Lambda Calculus
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      • ls command
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      • Manhattan Distance
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      • Markov blanket
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      • Markov Networks
      • Mask R-CNN
      • Matching and Ranking in Recommender Systems
      • Matrix
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      • Median
      • Message Queues
      • Meta-Learning
      • MFCC - Mel-Frequency Cepstrum Coefficients
      • Microservices
      • Microsoft Azure
      • MinIO
      • Minkowski Distance
      • mkdir command
      • MoCo V1 & V2
      • Mode
      • Model Fidelity for Explanation Models
      • Models for Multimodal Interaction
      • Moving Average
      • Multi Layer Perceptron
      • Multibiometric systems
      • Multimodal Coordination
      • Multimodal Fission
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      • NDCG - Normalized Discounted Cumulative Gain
      • Network Addressing
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      • Network Switching
      • Networking in Docker
      • Neural Network
      • Non-Linear Models
      • Normal Distribution
      • Object Detection
      • Object Search
      • Object Store
      • Obsidian useful commands
      • Open and Closed set identification
      • Operations with Sets in SQL
      • ORDER BY in SQL
      • Overfitting and Underfitting
      • PaaS - Platform as a Service
      • Paxos
      • PCA - Principal Component Analysis
      • Peer to Peer
      • Performance Evaluation in Biometric Systems
      • Person Search
      • Photoplethysmogram (PPG)
      • Pipe
      • Pointers in C
      • Polynomial Regression
      • Popularity Bias
      • Pose Forecasting
      • Possible spaces in which represent a face
      • Preprocessor Directives in C++
      • Primary Key
      • Prior Knowledge
      • Problems in biometrics systems
      • Problems of counterfactual explanation for time-series data
      • Process
      • Process APi in C
      • Process Mining
      • Proof of Stake
      • Proof of Work
      • Pseudonimity
      • Pub-Sub Messaging
      • Public Key Cryptography
      • Pump and Dump
      • Quantiles and Percentiles
      • R-CNN
      • RDD- Resilient Distributed Dataset in Spark
      • React Components
      • Recurrent Neural Networks (RNN)
      • Regular Inference
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      • Relationship between Bayesian Networks and Markov Random Fields
      • Reliability of an Identification System
      • REST
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      • Retrieval-Augmented Generation
      • RPC - Remote Procedure Call
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      • Social Navigation
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      • Sub-queries in SQL
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      • Swagger
      • Symmetrix matrix
      • Synchronous product of automata
      • t-test
      • Tanh Function
      • TCP-IP Stack
      • Temporal Convolutional Networks (TCN)
      • Terminology - History, Run, Local State, Global state, and Cut
      • Text-dependency and User-dependency in Biometric Systems
      • TF-IDF
      • The Blockchain Technology
      • The constant in O(c) is important
      • The Merge
      • The spectrum of Repair and Durability
      • The Stone-Weierstrass theorem
      • Threshold graph
      • Timed Automata
      • TOR - The Onion Router
      • touch command
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      • Transaction Model and UTXOs
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      • Vector Lengths and Distances
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      • Verification, Identification, Re-Identification, and Continuous Identification.
      • Vertex Cover Problem
      • Vertical vs Horizontal Scaling
      • Virtualization
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      • Wavelet Transform
      • What's a good counterfactual?
      • When to use DFS and BFS
      • WHERE and HAVING in SQL
      • Why are Functional Components better over Class Components in React
      • Why do we need multimodal interaction?
      • WIMP and Post-WIMP Interfaces
      • Word2Vec
      • Working with Dates in SQL
      • WWHT Model
      • Yabai Window Manager
      • Z-score
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        • Counterfactual Example Graph Search Reduction
        • ML Lifecycle.excalidraw
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    Descriptive Statistics

    Descriptive Statistics

    Nov 03, 2024, 1 min read

    • #math/statistics

    Descriptive Statistics deals with taking some data and describing it with values and plots in order to gain some insights about the data. Computing the mean and the percentiles is an example of descriptive statistics.

    This is different from Inferential Statistics.


    #math/statistics resources:

    • Introduction to Statistics (1.1) - YouTube

    Graph View

    Descriptive StatisticsQuantiles and PercentilesInferential Statistics#math/statisticsTopics - Statistics

    Backlinks

    • Topics - Statistics
    • Inferential Statistics

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