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Calculate arithmetic mean, weighted average, stock average & more instantly. Free average calculator for students, investors & professionals. Try it now — no signup.
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Last updated: April 2026 | Accurate for arithmetic mean, weighted averages, percentages & financial calculations
Numbers only tell the full story when you understand what's typical. Whether you're calculating your exam average, working out the mean return on a portfolio, finding an average electricity bill, or determining a stock's average purchase price — an average calculator gives you the answer instantly without error-prone manual addition and division.
Enter your values, choose your calculation type, and get your result in one click. No signup. No spreadsheet. No rounding mistakes.
This tool handles arithmetic mean, weighted averages, percentage averages, stock price averaging, time averages, and financial calculations — covering every practical scenario from a student calculating GPA to an analyst reviewing quarterly data.
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The average calculator is not a single-purpose tool. It covers the full range of average types used in real-world situations:
Each mode accepts multiple inputs and returns a clearly labelled result with the working shown — so you understand the calculation, not just the answer.
Direct answer: An average is a single number that represents the central or typical value of a dataset. The most common type is the arithmetic mean — calculated by dividing the sum of all values by the number of values.
Average = Sum of All Values ÷ Number of Values
The term "average" is used loosely in everyday language to mean "typical" or "normal." In mathematics and statistics, it refers specifically to the arithmetic mean — though several other types of average exist, each suited to different situations.
Averages reduce complex datasets to a single, meaningful number. Without them:
An average takes noise and gives you signal — the representative value from a set of varied data points.
Not all averages are the same. Using the wrong type can lead to misleading conclusions. Here are the four main types, when to use each, and how to calculate them.
What it is: The sum of all values divided by how many values there are. This is what most people mean when they say "average."
Formula: Mean = (x₁ + x₂ + x₃ + ... + xₙ) ÷ n
Example: Test scores: 72, 85, 91, 68, 79
Sum = 72 + 85 + 91 + 68 + 79 = 395 Count = 5 Mean = 395 ÷ 5 = 79
Best used for:
Limitation: The arithmetic mean is sensitive to extreme values (outliers). One very high or very low value can pull the mean significantly away from what's "typical."
What it is: A mean where some values count more than others, based on assigned weights. Essential when not all data points have equal importance.
Formula: Weighted Average = Σ(value × weight) ÷ Σ(weights)
Example: A student's final grade has these components:
| Assessment | Score | Weight |
|---|---|---|
| Homework | 85% | 20% (0.20) |
| Midterm | 78% | 30% (0.30) |
| Final Exam | 91% | 40% (0.40) |
| Participation | 100% | 10% (0.10) |
Weighted Average = (85×0.20) + (78×0.30) + (91×0.40) + (100×0.10) = 17 + 23.4 + 36.4 + 10 = 86.8%
A simple average of the four scores would give (85+78+91+100) ÷ 4 = 88.5% — a result that overweights participation and underweights the final exam, giving a misleadingly high grade.
Best used for:
Our Grade Calculator and GPA Calculator use weighted average logic specifically for academic performance tracking.
What it is: The middle value when all numbers are arranged in order. Exactly half the values fall above it and half below.
Formula:
Example (odd count): Dataset: 12, 45, 7, 89, 34 Sorted: 7, 12, 34, 45, 89 Median = 34
Example (even count): Dataset: 10, 20, 30, 40 Sorted: 10, 20, 30, 40 → Middle two: 20, 30 Median = (20 + 30) ÷ 2 = 25
Best used for:
For median-specific calculations across datasets, our Median Calculator handles this directly.
What it is: The value that appears most frequently in a dataset. A dataset can have no mode, one mode, or multiple modes.
Example: Dataset: 4, 7, 7, 9, 12, 7, 3, 9 Mode = 7 (appears 3 times — more than any other value)
Best used for:
For mode-specific analysis, our Mode Calculator handles single and multi-modal datasets.
| Average Type | Formula | Best For | Outlier Sensitivity |
|---|---|---|---|
| Arithmetic Mean | Sum ÷ Count | General data, scores, expenses | High |
| Weighted Mean | Σ(v×w) ÷ Σw | Grades, portfolios, surveys | High |
| Median | Middle value | Salaries, house prices | Low |
| Mode | Most frequent | Sales data, preferences | None |
Step 1 — List all values Write out every number in your dataset. Example: 15, 22, 8, 31, 19, 27
Step 2 — Add all values together 15 + 22 + 8 + 31 + 19 + 27 = 122
Step 3 — Count the values There are 6 numbers in the dataset.
Step 4 — Divide sum by count 122 ÷ 6 = 20.33
Result: The average is 20.33
For most practical purposes beyond 4–5 numbers, the calculator is faster and more reliable than mental arithmetic.
Averaging percentages is more nuanced than averaging plain numbers — and getting it wrong is surprisingly common.
Simple percentage average (equal weights): If all percentages are from datasets of equal size, simple averaging works.
Example — Exam scores: English: 80% | Maths: 90% | Science: 70% Average = (80 + 90 + 70) ÷ 3 = 80%
Weighted percentage average (unequal sizes): If the percentages come from different-sized groups, you must weight by group size.
Example — Survey response rates:
Wrong method: (75 + 90) ÷ 2 = 82.5%
Correct method: Weighted = (75×200 + 90×50) ÷ (200 + 50) = (15,000 + 4,500) ÷ 250 = 19,500 ÷ 250 = 78%
Office A's larger sample pulls the true average down. The simple average of 82.5% overestimates the actual combined response rate.
| Scenario | Values | Method | Result |
|---|---|---|---|
| 3 equal exams | 75%, 82%, 91% | Simple mean | 82.67% |
| 2 weighted courses | 80% (3 credits), 70% (1 credit) | Weighted | 77.5% |
| Pass rate (500 + 200 students) | 80%, 60% | Weighted by size | 74.3% |
For percentage-specific calculations, our Percentage Calculator handles conversions, percentage of totals, and percentage change.
When investors buy the same stock at different prices over time — a strategy called dollar-cost averaging (DCA) — they need to know their average purchase price to understand profit, loss, and break-even points.
Average Stock Price = Total Amount Invested ÷ Total Shares Purchased
| Purchase | Shares | Price/Share | Total Cost |
|---|---|---|---|
| January | 10 shares | $200 | $2,000 |
| March | 15 shares | $160 | $2,400 |
| June | 20 shares | $140 | $2,800 |
| Total | 45 shares | — | $7,200 |
Average Cost Per Share = $7,200 ÷ 45 = $160 per share
If the current price is $175:
Without knowing the average cost basis, investors can't accurately assess whether they're in profit or loss — especially after multiple purchases at different price points.
DCA naturally produces an average price lower than the arithmetic mean of the purchase prices. In the example above, the three prices average to (200+160+140)÷3 = $166.67 — but the actual average cost is $160, because more shares were purchased at the lower prices.
This is why DCA is a widely recommended long-term investment strategy — it mechanically produces a better average entry price without requiring market timing.
Average salary calculations:
A company's HR team wants to find the average salary across three departments:
| Department | Employees | Avg Salary |
|---|---|---|
| Engineering | 12 | $95,000 |
| Marketing | 8 | $72,000 |
| Sales | 15 | $68,000 |
Weighted average salary = (12×95,000 + 8×72,000 + 15×68,000) ÷ (12+8+15) = (1,140,000 + 576,000 + 1,020,000) ÷ 35 = 2,736,000 ÷ 35 = $78,171
Simple average of the three department averages would give (95,000+72,000+68,000)÷3 = $78,333 — close but not accurate, because it ignores the larger sales team.
US Salary Context:
For salary-specific tools, our Annual Income Calculator and Salary to Hourly Calculator convert between salary formats across pay periods.
Example — University GPA Calculation (US 4.0 scale):
| Course | Grade | Credits | Grade Points | Quality Points |
|---|---|---|---|---|
| English | A (4.0) | 3 | 4.0 | 12.0 |
| Maths | B+ (3.3) | 4 | 3.3 | 13.2 |
| Biology | A− (3.7) | 4 | 3.7 | 14.8 |
| History | B (3.0) | 3 | 3.0 | 9.0 |
| Total | — | 14 | — | 49.0 |
GPA = 49.0 ÷ 14 = 3.50
This is a weighted average where credit hours are the weights. A course worth 4 credits contributes twice as much to GPA as a 2-credit course — which is why failing a high-credit course has an outsized negative impact.
Monthly electricity bill averaging:
A household wants to know their average electricity bill across 12 months:
| Month | Bill |
|---|---|
| Jan | $145 |
| Feb | $138 |
| Mar | $112 |
| Apr | $98 |
| May | $87 |
| Jun | $94 |
| Jul | $122 |
| Aug | $131 |
| Sep | $105 |
| Oct | $97 |
| Nov | $118 |
| Dec | $142 |
| Total | $1,389 |
Monthly average = $1,389 ÷ 12 = $115.75
This average helps with monthly budget planning and year-on-year comparison. Pair with our Savings Goal Calculator to model how energy efficiency improvements affect annual spend.
Average steps per week:
Daily step counts over 7 days: 8,200 / 11,400 / 7,800 / 9,600 / 12,100 / 6,400 / 10,300
Sum = 65,800 ÷ 7 = 9,400 steps per day average
Just below the 10,000-step benchmark — useful for identifying trends before reviewing which days were low. Combine with our Steps to Miles Calculator to convert that average to daily distance covered.
Average calories burned per day:
If weekly calorie burns (from workout sessions) are: 320, 0, 450, 0, 380, 520, 0 Average = 1,670 ÷ 7 = 238.6 kcal/day — though this tells a misleading story (3 rest days pull the average down). Context matters when interpreting averages.
Average customer spend:
An eCommerce store processes 500 orders in a month with a total revenue of $47,350. Average order value = $47,350 ÷ 500 = $94.70
This single number drives numerous business decisions — pricing strategy, discount thresholds, upsell triggers, and shipping cost models.
Average time to resolve a support ticket: Resolutions in minutes: 12, 45, 8, 33, 67, 21, 14 Average = 200 ÷ 7 = 28.6 minutes
The median (21 minutes) is lower — indicating one or two long-tail resolutions are pulling the mean up. Both numbers together give a clearer picture of support performance than either alone.
The US context shapes how averages are applied across several specific domains:
| Role | US Average Salary (Approx 2024–2025) |
|---|---|
| Software Engineer | $115,000–$145,000/year |
| Registered Nurse | $75,000–$95,000/year |
| Teacher (K-12) | $55,000–$70,000/year |
| Accountant | $65,000–$85,000/year |
| Marketing Manager | $75,000–$110,000/year |
These are arithmetic means — subject to regional variation (San Francisco vs rural Midwest can differ by 40–60%) and outlier distortion from high-earner data.
| Utility | US Monthly Average |
|---|---|
| Electricity | ~$117–$140/month |
| Natural gas | ~$60–$90/month |
| Water | ~$40–$70/month |
| Internet | ~$55–$85/month |
| Total utilities | ~$272–$385/month |
(Sources: US Energy Information Administration and American Community Survey estimates)
Excel's built-in functions make average calculations fast and scalable for larger datasets.
Formula: =AVERAGE(A1:A10)
Returns the arithmetic mean of all values in cells A1 through A10. Ignores blank cells but includes zero values.
Formula: =AVERAGEIF(A1:A10, "<>0")
Returns the mean of only the non-zero values — useful when zeros represent missing data rather than actual zero measurements.
No single built-in function for weighted averages — but SUMPRODUCT handles it:
Formula: =SUMPRODUCT(B1:B5, C1:C5) / SUM(C1:C5)
Where B1:B5 = values and C1:C5 = weights.
Formula: =AVERAGEIF(A1:A20, ">50") Returns the average of only values greater than 50.
Formula: =AVERAGEIFS(B1:B20, A1:A20, "Engineering", C1:C20, ">2023") Returns the average of values in column B where column A = "Engineering" AND column C year > 2023.
To calculate a 3-period moving average starting at row 4: Formula in D4: =AVERAGE(C2:C4) Drag down to apply across subsequent rows.
Moving averages smooth out short-term fluctuations to reveal underlying trends — widely used in financial analysis and business reporting.
Average commute time over a week: Monday: 42 min | Tuesday: 38 min | Wednesday: 51 min | Thursday: 35 min | Friday: 44 min
Sum = 210 minutes ÷ 5 = 42 minutes average
But is 42 minutes the right benchmark? The median (42 min) coincides with the mean here — but on a week with an outlier (say, 120 minutes due to delays), the mean would jump to 58 minutes while the median might stay at 44 minutes. Always consider which measure best represents your situation.
Average speed is not simply the mean of two speeds when different distances are covered at each speed. This is the harmonic mean — one of the most commonly miscalculated averages.
Example:
Wrong (arithmetic mean): (60 + 30) ÷ 2 = 45 mph Correct (harmonic mean): 2 ÷ (1/60 + 1/30) = 2 ÷ (0.0167 + 0.0333) = 2 ÷ 0.05 = 40 mph
Check: 60 miles total ÷ 1.5 hours total = 40 mph ✓
The arithmetic mean overstates the average speed because it ignores that more time was spent at the slower speed.
A 7-day rolling average of daily sales smooths daily spikes and drops to reveal the underlying trend. If Monday through Sunday sales are $4,200 / $3,100 / $5,800 / $3,400 / $6,200 / $8,100 / $4,900:
7-day average = $35,700 ÷ 7 = $5,100/day
Next week, drop the oldest day and add the newest — giving a continuously updated trend figure without the noise of individual day variation.
| Calculation Type | Formula | Example | Result |
|---|---|---|---|
| Arithmetic Mean | Sum ÷ Count | (10+20+30) ÷ 3 | 20 |
| Weighted Average | Σ(v×w) ÷ Σw | (80×0.3)+(90×0.7) | 87 |
| Average % (equal) | Sum of % ÷ Count | (70+80+90) ÷ 3 | 80% |
| Average % (weighted) | Σ(rate×n) ÷ Σn | (80%×200 + 90%×50) ÷ 250 | 82% |
| Stock avg price | Total cost ÷ Total shares | $7,200 ÷ 45 | $160 |
| Average speed (equal dist) | 2ab ÷ (a+b) | 2(60×30) ÷ (60+30) | 40 mph |
| Moving average (3-period) | (x₁+x₂+x₃) ÷ 3 | (100+110+90) ÷ 3 | 100 |
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Averages are everywhere — in your payslip, your exam results, your investment portfolio, your energy bills, and your fitness tracker. Understanding which type of average to use, and calculating it correctly, is one of the most universally useful numerical skills in daily life.
The arithmetic mean handles most everyday situations. The weighted average gives you accuracy when some values matter more than others. The median protects you from outlier distortion. The mode tells you what's most common.
This calculator handles all of them — instantly, accurately, and without requiring any formula knowledge on your part.
Use it. Bookmark it. Share it with anyone who's ever wrestled with a set of numbers.
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All average calculations use standard mathematical formulas validated across arithmetic, weighted, and statistical contexts. Results are accurate to multiple decimal places. For large datasets with statistical analysis requirements, combine with the Standard Deviation Calculator for full descriptive statistics. Content is for educational and practical reference — financial averages cited are illustrative benchmarks from publicly available data sources.
Helpful answers related to this calculator.
An average is a single number representing the central or typical value of a dataset. The most common type is the arithmetic mean — calculated by adding all values and dividing by the count. Example: the average of 10, 20, and 30 is (10+20+30) ÷ 3 = 20. Other types include weighted average, median, and mode — each suited to different scenarios.
The standard average formula is: Average = Sum of All Values ÷ Number of Values. Example: values 5, 10, 15, 20, 25. Sum = 75. Count = 5. Average = 75 ÷ 5 = 15. For weighted averages, the formula is: Weighted Average = Σ(value × weight) ÷ Σ(weights).
If all percentages come from equal-sized groups, use the standard mean formula. Example: 70%, 80%, 90% → average = 80%. If groups are different sizes, weight each percentage by its group size: Weighted Average % = Σ(rate × group size) ÷ Σ(group sizes). Failing to weight percentages is one of the most common calculation errors in business and education.
A weighted average gives different values different importance levels based on assigned weights. Use it when some data points matter more than others — for example, a final exam worth 40% of a grade should count more than homework worth 10%. Formula: Σ(value × weight) ÷ Σ(weights). Standard averages assume equal importance for all values, which is often not the case.
Stock average price = Total money invested ÷ Total shares purchased. Example: Buy 10 shares at $100 and 20 shares at $80. Total invested = $1,000 + $1,600 = $2,600. Total shares = 30. Average price = $2,600 ÷ 30 = $86.67 per share. This is your cost basis — if the price rises above $86.67, you're in profit.
Mean is the arithmetic average (sum ÷ count). Median is the middle value when sorted. Mode is the most frequently occurring value. Example dataset: 2, 3, 3, 7, 10. Mean = 5. Median = 3. Mode = 3. Use mean for balanced datasets, median when outliers are present, mode for frequency analysis.
Use =AVERAGE(range). Example: =AVERAGE(A1:A10) returns the mean of values in cells A1 through A10. For weighted averages: =SUMPRODUCT(values_range, weights_range)/SUM(weights_range). For conditional averages: =AVERAGEIF(range, criteria). Excel ignores blank cells in AVERAGE calculations but includes cells containing zero.
The average (mean) US annual salary is approximately $63,000–$65,000 according to Bureau of Labor Statistics data. The median salary is lower, around $56,000–$58,000 — indicating that high earners pull the mean upward. Regional variation is significant: California and New York averages exceed $75,000, while many Midwestern and Southern states average $50,000–$55,000.
For equal time intervals: mean speed = (speed1 + speed2) ÷ 2. For equal distance intervals (different times): use the harmonic mean: average speed = (2 × s1 × s2) ÷ (s1 + s2). Example: 60 mph for 30 miles then 30 mph for 30 miles. Average speed = (2 × 60 × 30) ÷ (60 + 30) = 3600 ÷ 90 = 40 mph — not 45 mph as simple averaging would suggest.
An average calculator is mathematically exact — it performs the division to as many decimal places as specified. The limitation is not in the calculator but in the data: garbage in, garbage out. Ensure your inputs are correct, choose the right average type for your scenario (mean vs weighted vs median), and interpret the result in context. An accurate calculation of the wrong average type still produces a misleading answer.
In common usage, "average" typically refers to the arithmetic mean — so they're often interchangeable. Technically, "average" is a broader term covering mean, median, and mode, while "mean" specifically refers to the sum-divided-by-count calculation. In statistics, distinguishing which type of average is being reported is important — median household income and mean household income tell very different stories about a population.