Opportunity Through Data Textbook
  • Opportunity Through Data Textbook
  • Introduction
    • What is Data Science?
    • Introduction to Data Science: Exploratory Musical Analysis
  • Module 1
    • Introduction to Programming
      • The Command Line
      • Installing Programs
      • Python and the Command Line
      • Jupyter Notebook
    • Introduction to Python
      • Building Blocks of Python - Data Types and Variables
      • Functions
      • Formatting and Syntax
    • Math Review
      • Variables and Functions
      • Intro to Graphs
  • Module 2
    • Data Structures
      • Lists
      • Dictionaries
      • Tables
    • Programming Logic
      • Loops
      • Logical Operators
      • Conditionality
  • Module 3
    • Introduction to Probability
      • Probability and Sampling
    • Introduction to Statistics
      • Mean & Variance
      • Causality & Randomness
  • Module 4
    • Packages
    • Intro to NumPy
      • NumPy (continued)
  • Module 5
    • Introduction to Pandas
      • Introduction to Dataframes
      • Groupby and Join
    • Working with Data
    • Data Visualization
      • Matplotlib
      • Introduction to Data Visualization
  • Appendix
    • Table Utilities
    • Area of More Complicated Shapes
    • Introduction to Counting
    • Slope and Distance
    • Short Circuiting
    • Linear Regression
    • Glossary
  • Extension: Classification
    • Classification
    • Test Sets and Training Sets
    • Nearest Neighbors
  • Extension: Introduction to SQL
    • Introduction to SQL
    • Table Operations
      • Tables and Queries
      • Joins
  • Extension: Central Limit Theorem
    • Overview
    • Probability Distributions
      • Bernoulli Distribution
      • Uniform Distribution (Discrete)
      • Random Variables, Expectation, Variance
      • Discrete and Continuous Distributions
      • Uniform Distribution (Continuous)
      • Normal Distribution
    • Central Limit Theorem in Action
    • Confidence Intervals
  • Extension: Object-Oriented Programming
    • Object-Oriented Programming
      • Classes
      • Instantiation
      • Dot Notation
      • Mutability
  • Extension: Introduction to Excel
    • Introduction to Excel
      • Terminology and Interface
      • Getting Started with Analysis and Charts
      • Basics of Manipulating Data
    • Additional Features in Excel
      • Macros
      • The Data Tab
      • Pivot Tables
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  1. Extension: Central Limit Theorem
  2. Probability Distributions

Uniform Distribution (Continuous)

The continuous uniform distribution has an outcome space over a continuous range of values, each of which is equally likely to occur. Here is the PDF:

f(X=x)={1/(b−a),x∈[a,b]0,otherwisef(X = x) =\begin{cases}1/(b - a), &x \in [a, b]\\0, &otherwise\end{cases}f(X=x)={1/(b−a),0,​x∈[a,b]otherwise​

A real-world system this distribution can model is a perfect random number generator. Here, a is the lowest value allowed and b is the highest value allowed, meaning that the generator can produce any rational or irrational value between a and b, each with an equal probability.

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Last updated 4 years ago

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