Calculating Certain Properties from Distribution Functions

In summary, the problem involves using a distribution function f(x) to calculate the total number of objects and average value of a certain physical property x. The correct equations for these calculations are given, and it is noted that in some cases the property may only be defined for certain values of x. The process for calculating the median of the distribution is also discussed.
  • #1
MathIsFun
1. The problem statement, all variables, and given/known data
I am given a distribution function [itex]f(x)[/itex] that tells me the number of objects with a certain physical property [itex]x[/itex] (such as having a certain mass or temperature) and I need to calculate the total number of objects, the average value of the property of the objects, and values of [itex]x[/itex] that satisfy a certain value of [itex]f(x)[/itex].

Homework Equations


I don't know

The Attempt at a Solution


If the function [itex]f(x)[/itex] is defined on [itex]a<x<b[/itex], I believe the total number of objects would be [tex]\int_{a}^{b}f(x)\,dx[/tex] and the average value of the property would be [tex]\frac{\int_{a}^{b}x f(x)\,dx}{\int_{a}^{b}f(x)\,dx}[/tex]
First, are these correct?

Second, my main concern is that sometimes the property [itex]x[/itex] is defined only for values of [itex]x[/itex] in a set [itex]A[/itex] (e.g., counting). Since the distribution function is an approximation, does it still work for these values? For instance, if I had to calculate the value of the property [itex]x[/itex] that is held by [itex]n[/itex] objects and I get some value [itex]x=m\notin A[/itex], would I approximate it to the closest value that is in [itex]A[/itex], leave the answer as [itex]x=m[/itex], or say that there is no value of [itex]x\in A[/itex] that satisfies this condition?

Thank you
 
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  • #2
MathIsFun said:
First, are these correct?
They are correct.
The Census Bureau reports that the average American family in 2016 consists of 3.14 (no relation to π) persons. Does this answer your other question?
 
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  • #3
Yes, thank you.
 
  • #4
Now I have to calculate the median of the distribution. If [itex]f(x)[/itex] is defined for [itex]a<x<b[/itex], I would then calculate [tex]h(x)=\int_{a}^{x} \frac{f(z)}{N}\,dz[/tex], where [itex]N=\int_{a}^{b} f(x)\,dx[/itex], to get the cumulative distribution [itex]h(x)[/itex] and solve for [itex]x[/itex] when [itex]h(x)=0.5[/itex].
Is this correct?
 
  • #5
That is correct. For future reference, if you have a second question after the first one has been answered to your satisfaction, please post it separately. You may also post a multipart question, as in parts (a), (b), etc. if you plan ahead.
 
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What is the purpose of calculating properties from distribution functions?

Calculating properties from distribution functions allows us to understand and describe the behavior of a dataset. It can help us determine measures of central tendency, variability, and probability for a given distribution.

What are some common properties that can be calculated from distribution functions?

Some common properties that can be calculated from distribution functions include mean, median, mode, standard deviation, variance, skewness, and kurtosis.

How do you calculate the mean from a distribution function?

The mean of a distribution function can be calculated by finding the sum of all the data values and dividing by the total number of values in the dataset.

What is the difference between a continuous and a discrete distribution function?

A continuous distribution function is used to describe variables that can take on any value within a given range, such as height or weight. A discrete distribution function is used to describe variables that can only take on certain discrete values, such as the number of children in a family.

How can calculating properties from distribution functions be applied in real-world scenarios?

Calculating properties from distribution functions can be used in various fields such as economics, psychology, and engineering to analyze and interpret data. It can also be used to make predictions and inform decision making in areas such as risk management and quality control.

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