Calcolatore della distribuzione esponenziale
Calcola la PDF, la CDF e la media di una distribuzione esponenziale.
Piano di ammortamento
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Visualizzazione dei primi 12 di mesi.
Crescita nel tempo
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Introduzione
Exponential Distribution Calculator — Compute PDF, CDF, and mean of an exponential distribution. Enter Rate (λ), Value (x) to get an instant, accurate result.
Formula
PDF = λ × e^(−λx). CDF (probability that X ≤ x) = 1 − e^(−λx). Mean = 1/λ.
Passo dopo passo
- Enter the Rate (λ).
- Enter the Value (x).
- Click Calculate to see your result instantly.
Esempio pratico
Example: With Rate (λ) = 2, Value (x) = 1, the Exponential Distribution Calculator gives Pdf: 0.2707, Cdf: 0.8647, Mean: 0.5.
Domande Frequenti
What does the exponential distribution model?
It models the time between independent events that occur at a constant average rate, such as the waiting time until the next customer arrives.
What is the "memoryless" property?
The exponential distribution has no memory of elapsed time — the probability of waiting an additional t units is the same regardless of how long you've already waited.
What inputs does the Exponential Distribution Calculator need?
You'll need to provide: Rate (λ), Value (x). All fields use sensible defaults, so you can see a working example immediately and then adjust the values to match your own numbers.
How accurate is the Exponential Distribution Calculator?
The Exponential Distribution Calculator applies the formula exactly as calculated — PDF = λ × e^(−λx). CDF (probability that X ≤ x) = 1 − e^(−λx). Mean = 1/λ. — so results are precise for the inputs you provide. Accuracy depends on entering correct, realistic input values.
Is the Exponential Distribution Calculator free to use?
Yes, the Exponential Distribution Calculator is completely free, requires no signup, and runs instantly in your browser.
Informazioni su Calcolatore della distribuzione esponenziale
The Exponential Distribution Calculator uses a real, verifiable formula — PDF = λ × e^(−λx). CDF (probability that X ≤ x) = 1 − e^(−λx). Mean = 1/λ. — so results are accurate every time, not an approximation.