Maths Tool

Expected Value of Probability Density Function Calculator

Analyze continuous distributions using tabulated x and densities. See moments, normalization, variance, and weighted plots. Download clean reports for classes, audits, and probability work.

Calculator Input

Use one pair per line. Separate values with commas, spaces, tabs, or semicolons.

Example Data Table

This sample approximates a symmetric triangular density on the interval [0, 2]. The exact expected value is 1.

x f(x) x·f(x)
0.00.00.0
0.50.50.25
1.01.01.0
1.50.50.75
2.00.00.0

Formula Used

Continuous expectation: E[X] = ∫ x f(x) dx over the full support.

Normalization check: ∫ f(x) dx should equal 1 for a valid density.

Second moment: E[X²] = ∫ x² f(x) dx.

Variance: Var(X) = E[X²] − (E[X])².

This calculator uses the trapezoidal rule across the tabulated points. It approximates the areas under f(x), x·f(x), and x²·f(x).

How to Use This Calculator

  1. Enter paired x and density values in ascending x order.
  2. Use one row per point. Separate values clearly.
  3. Set the decimal precision for displayed results.
  4. Choose a target quantile if you want a percentile estimate.
  5. Submit the form to compute expectation and moments.
  6. Review the graph, summary cards, and contribution tables.
  7. Download CSV for spreadsheets or PDF for reporting.

Frequently Asked Questions

1. What does this calculator compute?

It estimates the expected value of a continuous random variable from tabulated density values. It also reports total area, second moment, variance, standard deviation, and an approximate quantile from the same data.

2. Why must the density stay nonnegative?

A probability density cannot be negative. Negative values would create invalid probability mass and distort the area, expected value, and all higher moments.

3. Does the total area need to equal one?

Yes, a valid density integrates to one. This tool still computes E[X] by dividing weighted area by total area, then reports the normalization gap so you can see any mismatch quickly.

4. How is the expected value approximated?

The tool applies the trapezoidal rule to the curve x·f(x). That numerical integral is divided by the integral of f(x), which gives an expected value estimate from your tabulated points.

5. Can I use irregular x spacing?

Yes. The x values do not need equal spacing. They only need to be strictly increasing so each interval width remains positive for the integration steps.

6. What does the quantile estimate mean?

It is the approximate x-value where the cumulative probability reaches your chosen probability level. For example, 0.50 returns an estimated median from the tabulated density.

7. Why include a graph?

The graph helps you inspect the density shape, the weighted curve x·f(x), and the cumulative distribution. Visual checks often reveal skewness, clipping, sparse sampling, or normalization issues.

8. When should I use more data points?

Use more points when the density changes rapidly or has curved sections. A denser grid usually improves the trapezoidal approximation and reduces numerical error.

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