What is the relationship between probability and calculus?

In summary, the probability of an exact value is analogous to a differential element of probability. This contradicts the fact that the sum of all events' probability is 1.
  • #1
1MileCrash
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In my probability class we were going over a method of visualizing probability as the area given two ranges of outcomes, for uncountable sample spaces.

But if we measure the outcome of an exact value, we get a line segment, which of course has an area of 0. But that value is in no way impossible.

Then I remembered that the sum of all events' probability is 1. So with an uncountably infinite amount of outcomes in a sample space, they must all sum to 1, yet when looking at one individually its probability is 0.

It kind of paralleled integral calculus to me in that the probability of an exact value is analogous to a differential element of probability. Can anyone shed some light on this idea?
 
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  • #2
1MileCrash said:
Then I remembered that the sum of all events' probability is 1. So with an uncountably infinite amount of outcomes in a sample space, they must all sum to 1, yet when looking at one individually its probability is 0.

So you reason that for all x in [0,1], we have [itex]P\{x\}=0[/itex]. So

[tex]1=P([0,1])=P\left(\bigcup_{x\in [0,1]} \{x\}\right)=\sum_{x\in [0,1]} P \{x\} = 0[/tex]

This is indeed a contradiction. But we made a mistake somewhere. Indeed, we did

[tex]P\left(\bigcup_{x\in [0,1]} \{x\}\right)=\sum_{x\in [0,1]} P \{x\}[/tex]

This is not valid since we are taking the union/sum over an uncountable set.

The [itex]\sigma[/itex]-additivity states that if [itex](A_n)_n[/itex] is a countable collection, then we have

[tex]P\left(\bigcup_n A_n\right)=\sum_n P(A_n)[/tex]

But this does not hold anymore for uncountable collections, as your example shows.

So while you can show that for every countable set [itex]A\subseteq [0,1][/itex], we have P(A)=0, we cannot do the same for uncountable sets.
 
  • #3
1MileCrash said:
It kind of paralleled integral calculus to me in that the probability of an exact value is analogous to a differential element of probability. Can anyone shed some light on this idea?

Have you studied probability density functions yet? They are the functions that are integrated to get the probability of events, so I suppose they could be a "differential element", depending on what you mean by that. They are the function that appear inside the integrand.
 

FAQ: What is the relationship between probability and calculus?

What is Calculus?

Calculus is a branch of mathematics that deals with finding and analyzing rates of change and the behavior of continuous functions. It has two main branches: differential calculus, which focuses on the study of rates of change, and integral calculus, which deals with the accumulation of quantities.

What is the importance of Calculus?

Calculus is used in many fields, including physics, engineering, economics, and statistics. It is essential for understanding concepts such as motion, optimization, and growth. Calculus also provides a foundation for more advanced mathematical concepts and is necessary for many scientific and technological advancements.

What is Probability?

Probability is a measure of the likelihood of an event occurring. It is a way to quantify uncertainty and is used in various fields, including statistics, economics, and physics. Probability is often expressed as a number between 0 and 1, where 0 represents impossibility and 1 represents certainty.

What is the difference between discrete and continuous probability?

Discrete probability deals with events that have a finite or countably infinite number of outcomes, such as rolling a die or flipping a coin. Continuous probability deals with events that have an infinite number of possible outcomes, such as measuring the height of a person or the temperature of a room.

How are Calculus and Probability related?

Calculus and probability are closely related, as probability theory uses concepts from calculus to analyze and model random phenomena. For example, the fundamental theorem of calculus is used in probability to calculate the probability of an event occurring within a certain range of values. Additionally, calculus is used to derive probability distributions and solve problems involving continuous probabilities.

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