# Average Calculator Compare arithmetic, geometric, and harmonic averages for a numeric dataset in one place > Canonical page: https://elysiatools.com/en/tools/average-calculator - **Category:** Math & Numbers - **Keywords:** average, mean, arithmetic mean, geometric mean, harmonic mean, statistics ## Overview The Average Calculator is a versatile statistical tool designed to compute and compare arithmetic, geometric, and harmonic means for any numeric dataset. Whether you are analyzing financial returns, speed metrics, or general data distributions, this tool provides instant calculations with customizable decimal precision and optional summary statistics. ## Inputs - **Dataset** (textarea): e.g. 4, 8, 16, 32 - **Average Type** (select) - **Decimal Places** (number) - **Include Summary Statistics** (checkbox) ## When to use - When you need to compare arithmetic, geometric, and harmonic means simultaneously to understand data distribution. - When analyzing financial portfolios, compound interest, or growth rates where a geometric mean is required. - When calculating the average of rates, ratios, or speeds where a harmonic mean provides the most accurate result. ## How it works - Paste or type your numeric dataset into the input field, separating numbers with commas or spaces. - Select the specific type of average you want to calculate, or choose to display all three types at once. - Adjust the decimal places for precision and toggle summary statistics if you need additional data insights. - View the calculated results instantly in a structured JSON format, ready for analysis or export. ## Use cases - Financial analysts calculating average portfolio returns and compound annual growth rates (CAGR). - Engineers and physicists determining average speeds, densities, or parallel resistance. - Students and researchers comparing central tendencies in skewed datasets. ## Frequently asked questions ### What is the difference between arithmetic, geometric, and harmonic means? The arithmetic mean is the sum of values divided by the count. The geometric mean multiplies values and takes the nth root, making it ideal for growth rates. The harmonic mean divides the count by the sum of reciprocals, which is best for averaging rates and ratios. ### How should I format my dataset? You can enter numbers separated by commas, spaces, or newlines. The tool will automatically parse the numeric values from your input. ### Can I change the number of decimal places in the result? Yes, you can adjust the decimal precision from 0 up to 10 places using the configuration options. ### What are the summary statistics included in the output? When enabled, summary statistics provide additional context about your dataset, such as the total count of numbers, sum, minimum, and maximum values. ### Why would I use the harmonic mean instead of a standard average? The harmonic mean is specifically useful when finding the average of rates or ratios, such as calculating the average speed of a vehicle traveling over equal distances at different speeds. ## Related tools - [Confidence Interval Calculator](https://elysiatools.com/en/tools/confidence-interval-calculator): Calculate confidence intervals for a sample mean or proportion using either raw data or summary statistics - [Geometric Mean Calculator](https://elysiatools.com/en/tools/geometric-mean-calculator): Calculate the geometric mean of positive numeric values for growth rates, ratios, and multiplicative datasets - [Harmonic Mean Calculator](https://elysiatools.com/en/tools/harmonic-mean-calculator): Calculate the harmonic mean of positive values, with optional arithmetic and geometric mean comparison - [Heat Exchanger LMTD Calculator (Log Mean Temperature Difference)](https://elysiatools.com/en/tools/heat-exchanger-lmtd): Compute the Log Mean Temperature Difference (LMTD) of a heat exchanger for parallel or counter flow. Parallel flow: ΔT₁ = T_h,in - T_c,in and ΔT₂ = T_h,out - T_c,out; counter flow: ΔT₁ = T_h,in - T_c,out and ΔT₂ = T_h,out - T_c,in. LMTD = (ΔT₁ - ΔT₂)/ln(ΔT₁/ΔT₂), or ΔT₁ when ΔT₁ = ΔT₂. A non-positive terminal difference (temperature cross) is physically impossible and is rejected. Optionally, with the overall heat transfer coefficient U (W/(m²·K)) and the heat transfer area A (m²), the heat transfer rate Q = U·A·LMTD (W) is returned. Temperatures are used only as differences: Δ°C = ΔK and Δ°F ×5/9 = ΔK; the LMTD is reported in K. - [Mean Calculator](https://elysiatools.com/en/tools/mean-calculator): Calculate the arithmetic mean of a numeric dataset and review the main supporting statistics - [Normal Distribution Calculator](https://elysiatools.com/en/tools/normal-distribution-calculator): Calculate z-scores, cumulative probability, tail probability, and interval probability for a normal distribution - [Sample Size Calculator](https://elysiatools.com/en/tools/sample-size-calculator): Estimate required sample size for proportions or means using confidence level, margin of error, and optional finite population correction - [Statistical Power Calculator](https://elysiatools.com/en/tools/statistical-power-calculator): Estimate statistical power for one-sample mean or proportion tests using sample size, alpha, and expected effect ## Samples - [Android Image Processing Java Samples](https://elysiatools.com/en/samples/android-image-processing-java): Android Java image processing examples including reading/saving images, scaling, and format conversion - [Android Image Processing Kotlin Samples](https://elysiatools.com/en/samples/android-image-processing-kotlin): Android Kotlin image processing examples including reading/saving images, scaling, and format conversion - [Web Image Processing Python Samples](https://elysiatools.com/en/samples/web-image-processing-python): Web Python image processing examples using PIL/Pillow including reading, saving, resizing, and format conversion - [Web Image Processing Rust Samples](https://elysiatools.com/en/samples/web-image-processing-rust): Web Rust image processing examples including image read/save, scaling, and format conversion