Help Needed: Calculating Geometric Mean Increase from 1998-2001

In summary, the purpose of calculating geometric mean increase is to determine the average rate of growth or change in a set of data over a specific period of time. It differs from other types of mean by taking into account the compounding effect of growth over time. To calculate it, a set of data with values for each year being analyzed is needed. However, it can be influenced by extreme values or outliers and assumes steady and continuous growth. The results can be interpreted as the average rate of growth, with a result greater than 1 indicating an increase and a result less than 1 indicating a decrease.
  • #1
bubble1421
1
0
I don't know why I can't figure this one out tonight. I just can't think straight and I am hoping someone can help ASAP.

Here is the question:
In 1998 revenue from gambling was $651 million. In 2001 the revenue increased to $2.4 billion. What is the geometric mean annual increase for the period?
 
Physics news on Phys.org
  • #2
Since the difference in the number of years is 3, you have to take the cube root of the ratio to get your result.
 
  • #3


First of all, don't worry about not being able to figure this out right away. Sometimes our minds just need a break and that's okay. Let's break down the problem together and hopefully we can come up with a solution.

To calculate the geometric mean increase, we need to first find the total growth rate for the period. This can be done by dividing the final value (in this case, $2.4 billion) by the initial value ($651 million). This gives us a growth rate of approximately 3.68.

Next, we need to find the number of years in the period. In this case, it is 3 years (1998-2001).

Now, we can use the formula for geometric mean increase, which is (1 + r)^1/n - 1, where r is the growth rate and n is the number of years.

Plugging in the values, we get (1 + 0.0368)^1/3 - 1, which simplifies to approximately 0.1158 or 11.58%.

Therefore, the geometric mean annual increase for the period is 11.58%.

I hope this helps and don't worry, we all have moments where our brains just need a little extra help. Keep practicing and you'll get the hang of it. Good luck!
 

Related to Help Needed: Calculating Geometric Mean Increase from 1998-2001

What is the purpose of calculating geometric mean increase from 1998-2001?

The purpose of calculating geometric mean increase is to determine the average rate of growth or change in a set of data over a specific period of time. In this case, it is used to analyze the change in values from 1998 to 2001.

How is geometric mean increase different from other types of mean?

Geometric mean increase differs from other types of mean, such as arithmetic mean, in that it takes into account the compounding effect of growth over time. It is calculated by taking the nth root of the product of n numbers, where n is the number of values being analyzed.

What data is needed to calculate geometric mean increase?

To calculate geometric mean increase, you will need a set of data with values for each year being analyzed (in this case, 1998 and 2001). The data should be in a format where you can easily calculate the product of the values (e.g. in a table or spreadsheet).

What are the limitations of using geometric mean increase?

One limitation of using geometric mean increase is that it can be heavily influenced by extreme values or outliers in the data. It also assumes that the growth or change is steady and continuous over the entire time period being analyzed.

How can the results of calculating geometric mean increase be interpreted?

The results of calculating geometric mean increase can be interpreted as the average rate of growth or change over the given time period. A result greater than 1 indicates an increase, while a result less than 1 indicates a decrease. The closer the result is to 1, the more stable and consistent the growth or change is.

Similar threads

Replies
2
Views
1K
  • Precalculus Mathematics Homework Help
Replies
10
Views
2K
  • Set Theory, Logic, Probability, Statistics
Replies
2
Views
1K
  • Set Theory, Logic, Probability, Statistics
Replies
5
Views
13K
Replies
5
Views
552
Replies
4
Views
2K
Replies
5
Views
1K
  • Set Theory, Logic, Probability, Statistics
Replies
7
Views
1K
Replies
7
Views
2K
Back
Top