1001Ferramentas
📐Calculators

Geometric Mean Calculator

Calculate the geometric mean of a list of positive numbers, ideal for growth rates, returns and indexes. Enter the values and see the result instantly.

GM

Geometric mean: the right average for growth rates

For n positive values, the geometric mean is GM = ⁿ√(x₁ · x₂ · … · xₙ). In practice you compute it as exp(mean of logs), which is more stable numerically. Use it when you're dealing with compound growth rates (CAGR) or any multiplicative quantity. Take returns of 2×, 8× and 32×: GM = ∛(2·8·32) = ∛512 = 8. The AM-GM inequality tells us GM is never larger than the arithmetic mean, and the two only match when every value is identical. That gap is exactly why averaging returns with the arithmetic mean flatters your compound performance. One caveat: the values have to be strictly positive, so for negatives you'll need a shift or a log-return transformation.

Applications

It shows up in financial returns (the annualized equivalent rate, fund performance), in population and economic growth (CAGR), in photometry and astronomy where you want a central value on a log scale, in antibody titers in biology, and in the UN Human Development Index (HDI). The HDI runs its three dimensions through the geometric mean precisely so that imbalance gets penalized.

FAQ

When use GM instead of arithmetic mean? Reach for it whenever the values multiply together: rates, ratios, percentage changes. Across several periods of returns, the GM hands you the equivalent constant rate. The arithmetic mean won't.

What if there are zeros or negatives? A single zero drags GM down to 0. Negatives leave the n-th root undefined when n is even. The fix for returns is to work with 1 + r rather than r, which keeps everything positive.

Why does HDI use GM? Because the geometric mean punishes imbalance. A country that's rich but poorly educated ends up scoring below one whose three dimensions are roughly level, which nudges the whole measure toward balanced development.

Related Tools

🎵

Harmonic Mean Calculator

Calculate the harmonic mean of a list of numbers, best suited for averaging rates, speeds and ratios. Enter the values and get the result instantly.

🌏

Geometric Asian Call (Kemna-Vorst)

Computes the price of a geometric-average Asian call option with the Kemna-Vorst closed form. Asian options pay based on the average price over the period, which reduces the impact of expiry manipulation and makes the premium cheaper. The geometric-average version has an exact solution: it's a Black-Scholes with volatility adjusted to σ/√3 and an adapted cost of carry. Enter the spot price, the strike, the interest rate, the term and the volatility.

📊

List Statistics

Calculate complete statistics for a list of numbers: sum, mean, median, mode, min, max, range and standard deviation.

🧮

Arithmetic Geometric Harmonic Mean Calculator

Computes arithmetic, geometric and harmonic means simultaneously for a list of positive numbers separated by comma.

📊

Cubic Mean Load (Bearing)

Calculate the equivalent mean load of a bearing under a cycle with two different loads, P_m = ∛(P₁³·U₁ + P₂³·U₂), from the loads P₁ and P₂ (N) and the time (or revolution) fractions during which they act U₁ and U₂ (with U₁ + U₂ = 1). Many bearings do not work under CONSTANT load: the load varies over the operating cycle (a press loading and unloading, a motor accelerating and decelerating, a machine with different work phases). To compute life in this case, the variable cycle is replaced by an equivalent CONSTANT load causing the same fatigue damage — the mean load. But the mean is NOT arithmetic: since fatigue damage is proportional to load CUBED (the life exponent p=3), the mean load is a time-fraction-weighted mean, but with the loads cubed (then cube-rooted) — the so-called cubic mean or 'fatigue-weighted mean'. This makes HIGH loads weigh disproportionately more (a double load causes 8× more damage), so even a small fraction of time at high load dominates the result. This formula (here for two load levels; it generalizes to several) is essential to size bearings in variable-load machines, avoiding underestimating the damage. Enter the two loads and their time fractions.

📊

Z-Test for a Mean (Known σ)

Computes the z-test for a mean when the population standard deviation is known. It's the simplest case of hypothesis testing about a mean: the statistic measures how many standard errors separate the observed mean from the hypothesized value. When σ is known (or the sample is large), the normal distribution is used instead of the t. The tool returns the z statistic and the two-sided p-value. Enter the sample mean, the hypothesized mean, the population standard deviation and the sample size.

The results provided by this tool are for general informational and educational purposes only and do not constitute professional, financial, medical, legal, tax or accounting advice. Always confirm important decisions with a qualified professional and official sources.