Continuous distribution
A continuous distribution is a probability distribution for a variable whose possible values form a continuous range rather than a discrete set.
Grokking Statistics
A continuous distribution is a probability distribution whose variable can take values across a continuous range rather than only distinct countable values.
- How it is used
- Models measured quantities and uncertain rates as values across a range rather than separate outcomes.
- How deep it goes
- Explains density, total area, exact-value probability, and CDF subtraction without calculus.
- Examples
- Uses success rates, coffee-ground measurements, and golden retriever weights to contrast curves, densities, and interval areas.
- What you can do after
- Apply it via SciPy to plot densities and calculate probabilities over value ranges with CDFs.
Read how Grokking Statistics explains continuous distribution →
Fabulous Adventures in Data Structures and Algorithms
A continuous distribution assigns probabilities over values in a continuous range.
- How it is used
- Models and samples random real-valued quantities in simulations and probabilistic reasoning.
- How deep it goes
- Defines PDFs, normalization, CDFs, quantiles, and sampling methods, while deferring arbitrary posterior sampling to Markov-based methods.
- Examples
- Uses beta densities, manufacturing measurements, uniform samples, C# distribution objects, and vertical histograms.
- What you can do after
- Evaluate and understand real-valued probabilities, then apply inverse-transform or rejection sampling when the necessary distribution information is available.
Read how Fabulous Adventures in Data Structures and Algorithms explains continuous distribution →
Related concepts
- beta distributionincludes · A beta distribution is a continuous probability distribution on the interval [0,1], parameterized by two positive shape parameters.
- uniform distributionincludes · A uniform distribution assigns equal probability to each outcome in a discrete support or constant probability density across a continuous interval.
- probability distributionkind of · A probability distribution is a mathematical specification assigning probabilities to the possible values or outcomes of a random variable, with total probability one.
- Bayes' theoremused by · Bayes' theorem is a probability rule that expresses a conditional probability in terms of a prior probability, a likelihood, and the evidence.
- exponential distributionincludes · The exponential distribution is a continuous probability distribution over nonnegative values with an exponentially decreasing density, commonly modeling waiting times between events in a constant-rate Poisson process.
- normal distributionincludes · A normal distribution is a continuous probability distribution with a symmetric, bell-shaped density determined by its mean and variance.
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