Histogram of Sinusoid: Is it the Same as PDF?

  • Thread starter Thread starter X1088LoD
  • Start date Start date
  • Tags Tags
    Histogram Pdf
AI Thread Summary
The histogram of a sinusoid represents an approximation of its probability density function (PDF) when derived from experimental data. To accurately approximate the PDF, the histogram must be normalized by dividing the frequency of each bin by the total number of data points. For continuous data, bins should represent ranges of values rather than single points to enhance accuracy. Using more bins or smaller ranges improves the approximation of the true underlying PDF. Thus, while a histogram can approximate the PDF, it requires proper standardization and binning to achieve this.
X1088LoD
Messages
21
Reaction score
0
I am looking at values of a sinusoid, y = A sin(2*Pi*f*t), oscillating between A and -A at a frequency of 25 Hz over 0.650 milliseconds.

If I find the histogram of the sinusoid, is this the same thing as the probability density function of that sinusoid? If this is not the case, what does the histogram represent in terms of statistical analysis?

I appreciate it.

~ Brent Ellis
 
Physics news on Phys.org
The histogram is a representation of the probability density function. If you get it by some experimental menas, it is an approximation. If you get it from theory, then it will be exact if you don't average over intervals (sorting into bins is what a histogram usually refers to).
 
so let's say I got my data by means of measurements, 4096 data points total, then i sort them into histogram form

If each bin is represented by 1 value, If I divide each point by 4096, would that normalize the plot into the actual (approximation) PDF?
 
If the data you have collected is continuous, which i think is the case, then you can't let one bin represent one value, it has to be a range of values. The smaller the range of values, or the larger the number of bins you use, the closer you will get to approximating the true underlying pdf. Of course, the histogram has to be standardized so that the y-axis represents a proportion of observations per bin, so divide the frequencies of each bin by 4096.
 
I was reading a Bachelor thesis on Peano Arithmetic (PA). PA has the following axioms (not including the induction schema): $$\begin{align} & (A1) ~~~~ \forall x \neg (x + 1 = 0) \nonumber \\ & (A2) ~~~~ \forall xy (x + 1 =y + 1 \to x = y) \nonumber \\ & (A3) ~~~~ \forall x (x + 0 = x) \nonumber \\ & (A4) ~~~~ \forall xy (x + (y +1) = (x + y ) + 1) \nonumber \\ & (A5) ~~~~ \forall x (x \cdot 0 = 0) \nonumber \\ & (A6) ~~~~ \forall xy (x \cdot (y + 1) = (x \cdot y) + x) \nonumber...
Back
Top