Please help explain the probability density function

In summary, the given equations demonstrate the relationship between energy, position, and time for a simple harmonic oscillator. The equation for velocity, derived from the energy equation, is also shown. The question then discusses the connection between time and position, specifically in relation to the period of the oscillator. The probability density function is used to define the probability of being in a certain position, taking into account the time spent in that position.
  • #1
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##E = \frac{1}{2}(kx^2+m \dot{x}^2)##
## \frac{2E - kx^2}{m}=\dot{x}^2##
##\frac{dx}{dt} = \sqrt{\frac{2E - kx^2}{m}}## or ## dt = \sqrt{\frac{m}{2E - kx^2}}dx ## ⇒##= \frac{1}{\sqrt{\frac{2E - kx^2}{m}}}dx##

My Question please help me.
1. I know ##T = 2\pi\sqrt{\frac{m}{k}} .## but i don't understand why ##T = 2 \int_{-l}^{l}\frac{1}{\sqrt{\frac{2E - kx^2}{m}}}dx##2.In this case. Why do we choose the probability density function, ## p(x) = \frac{2dt}{T} ## ?
 

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  • #2
I don't understand how to define the probability density function.
 
  • #3
1. The denominator is the speed at position x (see the equation for E). The time dt spent in the interval dx is dx/vx.
2. The probability of being between x and x+dx equals the fraction of the time that is spent in this interval, i.e. 2dt/T (2 because it traverses this interval twice in a full period), where dt is related to dx as above.
 
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1. What is a probability density function (PDF)?

A probability density function (PDF) is a mathematical function that describes the probability of a continuous random variable taking on a specific value. It is used to model and analyze data that follows a continuous distribution, such as the normal distribution.

2. How is a PDF different from a probability distribution function (PDF)?

A PDF is a function that describes the probability of a continuous random variable taking on a specific value, while a probability distribution function (PDF) is a function that describes the probability of a discrete random variable taking on a specific value. In other words, a PDF is used for continuous data, while a PDF is used for discrete data.

3. What is the area under a PDF curve?

The area under a PDF curve represents the total probability of all possible outcomes. This area is always equal to 1, as the probability of all possible outcomes must add up to 100%.

4. How is the mean and standard deviation related to a PDF?

The mean and standard deviation of a PDF are important measures that describe the central tendency and spread of the data, respectively. The mean is the average value of the data and is represented by the peak of the PDF curve. The standard deviation is a measure of how much the data deviates from the mean and is represented by the width of the PDF curve.

5. How is a PDF used in statistical analysis?

A PDF is used in statistical analysis to calculate probabilities and make predictions about the data. It can also be used to compare different datasets and determine how well they fit a particular distribution. Additionally, a PDF can be integrated to find the probability of a random variable falling within a certain range of values.

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