Geometric average versus arithmatic average

In summary, the conversation discusses finding a new set of normalized weights that can be used to calculate the arithmetic average of a set of numbers, while also being equal to the geometric average. The weights are currently unequal and may need to be adjusted to achieve this equality. One suggestion is to have all weights be equal in order to achieve this balance.
  • #1
Niles
1,866
0

Homework Statement


I have a range of numbers numbers [itex]n_i[/itex], each with a different weight [itex]w_i[/itex] that sum up to 1. To keep things simple, let's take the case where we have three numbers with the following weights:

n_i w_i
------------------------------
100 0.5
30 0.2
20 0.3

Their geometric average is [itex](100^{0.5})*(30^{0.2})*(20^{0.3})=48.4991[/itex]. The arithmetic average of the numbers is [itex]100*0.5 + 30*0.2 + 20*0.3=62[/itex], so it is larger than the geometric average.

How can I find a new set of normalized weights [itex]w_i'[/itex] that sum to 1 that can be used to find the arithmetic average of the numbers such that it is equal to the geometric average? In other words, I would like to find a new set [itex]w_i'[/itex] such that

[itex]100*w_1' + 30*w_2' + 20*w_3' = (100^{0.5})*(30^{0.2})*(20^{0.3})[/itex] given that [itex]w_1'+w_2'+w_3'=1[/itex].

The weights are all nonzero.My best attempt at the moment is

[tex]
\sum_i (\text{GA} \frac{w_i}{n_i}) n_i
[/tex]

where GA is the geometric average. This sum yields GA as expected, but the weights are larger than 1.
 
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  • #2
Unweighted, the arithmetic mean is always >= geometric mean, so I suspect your weights may have to have a sum > 1. Think what happens if one of the numbers you're averaging is zero.
 
  • #3
To get equality between AM and GM, you need all terms equal. What does that suggest for the weights? You can always get the weights to add to 1 by normalising: divide by the sum of the weights.
 

What is the difference between geometric average and arithmetic average?

The geometric average is a type of mean that takes into account the compounding effect of growth over time, while the arithmetic average is a simple average of values. Geometric average is used for data sets that show exponential growth or decay, while arithmetic average is used for data sets that show linear growth or decline.

When should I use geometric average versus arithmetic average?

Geometric average should be used when analyzing data sets that have exponential growth or decay, such as investment returns or population growth. Arithmetic average should be used for data sets that have linear growth or decline, such as test scores or daily temperature readings.

How is geometric average calculated?

To calculate the geometric average, multiply all values in the data set and then take the nth root of the product, where n is the number of values in the data set. For example, to calculate the geometric average of 2, 4, and 8, you would multiply 2 x 4 x 8 = 64 and then take the cube root of 64, which is 4.

How is arithmetic average calculated?

To calculate the arithmetic average, add all values in the data set and then divide by the number of values. For example, to calculate the arithmetic average of 2, 4, and 8, you would add 2 + 4 + 8 = 14 and then divide by 3 (the number of values), which equals 4.67.

Can geometric average and arithmetic average be used interchangeably?

No, geometric average and arithmetic average cannot be used interchangeably. They are two different types of means that are used for different types of data sets. Using the wrong type of average can result in misleading or inaccurate conclusions about the data.

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