Geometry/statistics problem

  • Thread starter ManuelCalavera
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In summary, the conversation discusses a math/statistics problem where a square with side lengths W contains randomly distributed circles with varying diameters according to a Gaussian distribution. The goal is to find the mean value of the diameter that will maximize the number of circles that can fit in the square without overlapping. The circles are assumed to be a random sample from the same Gaussian distribution with a chosen mean and set standard deviation, and there is a minimum mean value that can be chosen. There are still some issues with the formulation of the problem, but it is believed that the minimum mean value will always minimize the areal density regardless of how the circles are chosen or placed in the square.
  • #1
ManuelCalavera
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Hi,

I'm not sure if this is the right forum to put this question in as it's not a homework problem but it is a math/statistics problem. I'm really not sure how to even start.

So the problem is this:
You have a square with side lengths W and circles that have diameter's that are randomly distributed according to the Gaussian distribution. You can choose the mean of the distribution but the standard dev is set. There is a minimum mean value.

You want to find the mean value of the diameter that will maximize the amount of circles you can fit in the square. The circles can't overlap and they must be whole circles. I'm almost sure it is the minimum value so I guess I just have to prove that.

My background is in engineering/physics so I don't have a first principles math education so I'm really not sure how to even begin the problem.

Thanks for any help (and sorry if this is in the wrong place)
 
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  • #2
ManuelCalavera said:
Hi,

I'm not sure if this is the right forum to put this question in as it's not a homework problem but it is a math/statistics problem. I'm really not sure how to even start.

So the problem is this:
You have a square with side lengths W and circles that have diameter's that are randomly distributed according to the Gaussian distribution. You can choose the mean of the distribution but the standard dev is set. There is a minimum mean value.

You want to find the mean value of the diameter that will maximize the amount of circles you can fit in the square. The circles can't overlap and they must be whole circles. I'm almost sure it is the minimum value so I guess I just have to prove that.

My background is in engineering/physics so I don't have a first principles math education so I'm really not sure how to even begin the problem.

Thanks for any help (and sorry if this is in the wrong place)

There are several issues at fault with your formulation, but perhaps they can be corrected, or at least, clarified.
(1) By "quantity of circles", do you mean number of circles, or total area covered by circles?
(2) Are all the circles (a) identical in size, or (b) are they a random sample of independently-chosen circles that are all drawn from the same Gaussian distribution of radius?
(3) If the circles' radii are random, the area covered is a random quantity, so what can you possibly mean by maximizing it? A similar objection occurs if you want to maximize the number of circles that fit in the square.
 
  • #3
Ray Vickson said:
There are several issues at fault with your formulation, but perhaps they can be corrected, or at least, clarified.
(1) By "quantity of circles", do you mean number of circles, or total area covered by circles?
(2) Are all the circles (a) identical in size, or (b) are they a random sample of independently-chosen circles that are all drawn from the same Gaussian distribution of radius?
(3) If the circles' radii are random, the area covered is a random quantity, so what can you possibly mean by maximizing it? A similar objection occurs if you want to maximize the number of circles that fit in the square.
Hi,

Thanks for replying. To answer your questions:

1) The areal density, the number of circles per unit area
2) The assumption is that they are taken from a random sample of independently chosen circles that are drawn from the same Gaussian distribution, with a chosen mean and set sigma.
3) You have some discrete amount of circles whose radii is sampled from a gaussian distribution. You're trying to pick a mean value to maximize the areal density. And there is a minimum mean value you can choose.

I think there might still be issues with the formulation of the problem. I think you might be able to get around some of them because I'm almost sure the minimum mean value will always minimize the areal density regardless of how circles are chosen or are placed in the square.

Thanks again
 

1. What is the difference between geometry and statistics?

Geometry is a branch of mathematics that deals with the study of shapes, sizes, and their properties. Statistics, on the other hand, is a branch of mathematics that deals with the collection, analysis, interpretation, presentation, and organization of data.

2. How are geometry and statistics related?

Geometry is used in statistics to visualize and represent data in the form of graphs, charts, and diagrams. Statistics, in turn, helps in making predictions and drawing conclusions about the data using various geometric concepts, such as measures of central tendency and dispersion.

3. What are some common applications of geometry in statistics?

Some common applications of geometry in statistics include constructing histograms, scatter plots, and box plots to represent data, calculating measures of central tendency and dispersion using geometric formulas, and using geometric models to make predictions and estimate probabilities.

4. What are the different types of geometric shapes used in statistics?

The most commonly used geometric shapes in statistics include lines, circles, rectangles, triangles, and polygons. These shapes are used to represent data and make calculations, such as finding the area and perimeter of a graph or calculating the standard deviation of a set of numbers.

5. How can understanding geometry help in solving statistical problems?

A strong understanding of geometry can help in visualizing and manipulating data, making accurate calculations, and interpreting results in statistics. It also provides a framework for understanding and applying various statistical concepts and methods, such as regression analysis and hypothesis testing.

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