Why are there more zeros in a sine wave than 1s and -1s?

In summary, the conversation discusses the frequency of zeros in a function, particularly a sine wave. It is mentioned that the zeros of a function are the roots or positions where the function equals 0. The frequency of zeros is found to be twice as frequent as the frequency of the peaks and troughs. The concept of probability density is also brought up, with the understanding that the value of the pdf at a specific point cannot be interpreted as how often it takes that value. It is also explained that the curve spends more time near the peaks and less time near the x=0 line, which explains why the zeros are less frequent. The conversation ends with the speaker expressing gratitude for the clarification.
  • #1
dexterdev
194
1
Hello guys,
From a layman's viewpoint when we count occurrences of different amplitude values, then frequency of zeros must be maximum is not it? but it is as below:

pdf.png


why so? zeoros must be maximum, 1s and -1s are lesser than 0 isn't it?
 
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  • #2
"frequency of zeros must be maximum"?

The zeros of a function are the roots.
Positions x: f(x)=0.

In f(t)=sin(wt) the frequency is w, the amplitude is 1, and the zeros are twice as frequent as that.

The values that |sin(wt|=1 is the same frequency as the the frequency of the zeros ... but the peaks and the troughs appear only as frequently as w.

This what you are saying?
I think you need to revisit, carefully, how the graph was derived and what it actually means. I'm not sure it is telling you what you think it does.
eg. I think the frequency of occurance of the number of points of intersection between y=f(x) and y=k is the same for every k except for |k|=1 - where it is half.
 
  • #3
Your question is very unclear, but your graph illustrates that a sine function spends much longer vicinity of 1 and -1 rather than in the vicinity of 0. Is that surprising?
 
  • #4
Remember the slope of the inverse is reciprocal of slope of the function.
what you state is true for derivative of sine, it will be opposite for derivative of arcsine.
Especially slope of sine is 0 at (pi/2,1) so slope of arcsine approaches infinity at (1,pi/2).
 
  • #5
haruspex said:
Your question is very unclear, but your graph illustrates that a sine function spends much longer vicinity of 1 and -1 rather than in the vicinity of 0. Is that surprising?
Oh is that what it is - illustrating hang-time?!
 
  • #6
The probability density of a steady sine-wave ' Asin (wt) ' is not
bell-shaped, since it spends more time near the peaks than near x = 0; it extends
only over -A ≤ x ≤ +A (it is zero outside that range) and spikes at the maximum
positive and negative values. (lines from moretti.ceat.okstate.edu/MAE5073/Prob1801.pdf)

but how?


These are the lines of confusion for me. My idea of pdf is that it gives peaks for higher probability values. But for a sine wave why is zeros lesser, it must be maximum. consider one cycle of sine wave. We have one peak A, one negative peak -A and 2 zeroes (3rd zero for next cycle). Is my calculus bad? If my basic idea is wrong , please can anyone kindly explain it to me (in very simple english). You people are my strength, truely.

TIA
 
  • #7
dexterdev said:
The probability density of a steady sine-wave ' Asin (wt) ' is not bell-shaped, since it spends more time near the peaks than near x = 0; it extends
only over -A ≤ x ≤ +A (it is zero outside that range) and spikes at the maximum
positive and negative values. (lines from moretti.ceat.okstate.edu/MAE5073/Prob1801.pdf)

My idea of pdf is that it gives peaks for higher probability values. But for a sine wave why is zeros lesser, it must be maximum. consider one cycle of sine wave. We have one peak A, one negative peak -A and 2 zeroes (3rd zero for next cycle).
For a continuous distribution, the value of the pdf at some point x cannot be interpreted as how often it takes the value x. The probability of getting exactly x is zero. Instead, think of it as the probability of getting a value in a small range about x.
If you take a thin horizontal band through a sine wave around the y=0 line, the curve doesn't spend long in the band. It enters the band every pi, but passes through quickly. A similar band at y=1 is entered half as often, but the curve spends much longer in the band each time.
 
  • #8
Thankyou sir, you saved my life. I don't why doubts are haunting me like this.

Thanks again
 

Related to Why are there more zeros in a sine wave than 1s and -1s?

1. Why is the sine wave considered a probability density function (pdf)?

The sine wave is considered a pdf because it can be used to model the probability distribution of various natural phenomena, such as sound and light waves. It is also a continuous function that satisfies the properties of a pdf, including being non-negative and integrating to one over its domain.

2. How is the sine wave related to probability and statistics?

The sine wave is related to probability and statistics through its use as a pdf. In probability theory, the area under the curve of a pdf represents the probability of a random variable falling within a certain range of values. In statistics, the sine wave is used to model a variety of continuous data, making it a useful tool for analyzing and interpreting data.

3. Why is the sine wave so commonly used in scientific research and experiments?

The sine wave is commonly used in scientific research and experiments because it is a fundamental function that can be used to describe a wide range of natural phenomena. It also has many useful properties, such as being periodic and smooth, making it a useful tool for analyzing and understanding complex systems and data.

4. How does the shape of the sine wave affect its use as a pdf?

The shape of the sine wave, which is a smooth, oscillating curve, makes it a good fit for modeling many natural phenomena that exhibit similar patterns. Its periodic nature also allows for easier calculations and predictions in certain situations. However, it may not accurately represent all types of data, so it is important to carefully consider its use in each specific case.

5. Can other functions besides the sine wave be used as pdfs?

Yes, there are many other functions that can be used as pdfs, depending on the type of data being analyzed. Some common examples include the normal (Gaussian) distribution, exponential distribution, and beta distribution. The choice of which function to use depends on the characteristics of the data and the specific research question being addressed.

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