When a data set contains a large number of repeated values, you can simplify the process of computing the mean by using weights — the frequencies of a value in a sample or a population. You can then compute the geometric mean as a weighted average.
You can calculate the weighted geometric mean in the same way for both samples and populations. The formula is:
![image0.png](https://cdn.prod.website-files.com/6634a8f8dd9b2a63c9e6be83/6698d6c8a720f5494aaaa22c_460071.image0.png)
Here's the breakdown of this equation:
![image1.png](https://cdn.prod.website-files.com/6634a8f8dd9b2a63c9e6be83/6698d6c8a720f5494aaaa232_460072.image1.png)
You apply an exponent to each element in the data set that equals the weight of the element. You then multiply these values together and raise to a power equal to one divided by the sum of the weights.
An exponent is the superscript in an expression such as 34; in this case, the base is 3 and the exponent is 4. This is shorthand for multiplying 3 by itself four times:
![image2.png](https://cdn.prod.website-files.com/6634a8f8dd9b2a63c9e6be83/6698d6c8a720f5494aaaa239_460073.image2.png)
Note that in many formulas and Microsoft Excel, the asterisk (*) represents multiplication. In Excel the carat (^) represents exponentiation.
As an example, a marketing firm conducts a survey of 20 households to determine the average number of cellphones each household owns. Here's the sample data from this survey:
Number of Cell Phones Per Household | Number of Households |
---|---|
1 | 2 |
2 | 5 |
3 | 6 |
4 | 4 |
5 | 3 |
To figure out the weighted geometric mean, follow these steps:
Compute the value of each Xi with an exponent equal to its weight wi:
Multiply these results together:
Divide 1 by the sum of the weights:
Combine these results to find the weighted geometric mean:
So on average, each household has approximately 2.78 cellphones.