Average Calculator
Calculate the arithmetic mean (average) of up to 50 numbers with step-by-step solutions
Enter Your Values
You can enter up to 50 values. Fields will appear automatically as you fill them in.
Results
Example Calculation
Test Scores Example
Problem: Find the average test score
Scores: 85, 92, 78, 96, 88, 74, 91
Number of scores: 7
Solution
Step 1: Add all values: 85 + 92 + 78 + 96 + 88 + 74 + 91 = 604
Step 2: Count the values: n = 7
Step 3: Calculate average: 604 ÷ 7 = 86.29
Average test score = 86.29
Types of Averages
Arithmetic Mean
Sum of values ÷ Count
Most common type of average
Median
Middle value when sorted
Less affected by outliers
Mode
Most frequently occurring value
Useful for categorical data
Quick Tips
The average is also called the arithmetic mean
Outliers can significantly affect the average
Use median when data has extreme values
Enter decimals for more precise calculations
Fields automatically expand as you type
Understanding Averages
What is an Average?
An average, also known as the arithmetic mean, is a measure of central tendency that represents the typical value in a dataset. It's calculated by adding all the values together and dividing by the total number of values.
When to Use Averages
- •Comparing groups of data (test scores, temperatures, etc.)
- •Finding typical performance or behavior
- •Summarizing large datasets with one number
- •Statistical analysis and research
Average Formula
Average = Sum ÷ Count
Mean = (x₁ + x₂ + x₃ + ... + xₙ) ÷ n
Limitations of Averages
- ⚠Sensitive to extreme values (outliers)
- ⚠May not represent any actual data point
- ⚠Can be misleading with skewed distributions
Pro Tip: Always consider the median and range alongside the average for a complete picture of your data.
Common Applications
Academic
- • Grade point averages (GPA)
- • Test score analysis
- • Class performance metrics
- • Research data analysis
Business
- • Sales performance
- • Customer satisfaction scores
- • Revenue per customer
- • Employee productivity
Daily Life
- • Budgeting and expenses
- • Sports statistics
- • Weather data
- • Health metrics