Histogram of Sinusoid: Is it the Same as PDF?

  • Context: Undergrad 
  • Thread starter Thread starter X1088LoD
  • Start date Start date
  • Tags Tags
    Histogram Pdf
Click For Summary
SUMMARY

The histogram of a sinusoid, defined by the equation y = A sin(2*Pi*f*t) with a frequency of 25 Hz over 0.650 milliseconds, serves as an approximation of its probability density function (PDF). Brent Ellis clarifies that if the histogram is derived from experimental data, it approximates the PDF, while theoretical derivations yield exact results without binning. To normalize the histogram into an approximation of the PDF, one must divide the frequency of each bin by the total number of data points, which is 4096 in this case. Additionally, using a larger number of bins improves the approximation of the true underlying PDF.

PREREQUISITES
  • Understanding of sinusoidal functions and their properties
  • Familiarity with histograms and their construction
  • Knowledge of probability density functions (PDFs)
  • Basic statistical analysis techniques
NEXT STEPS
  • Study the construction and interpretation of histograms in statistical analysis
  • Learn about the relationship between histograms and probability density functions
  • Explore techniques for normalizing histograms for accurate PDF approximation
  • Investigate the impact of bin size on histogram accuracy and PDF representation
USEFUL FOR

Statisticians, data analysts, and anyone involved in signal processing or statistical modeling who seeks to understand the relationship between histograms and probability density functions.

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.
 

Similar threads

  • · Replies 3 ·
Replies
3
Views
8K
  • · Replies 5 ·
Replies
5
Views
3K
  • · Replies 1 ·
Replies
1
Views
4K
  • · Replies 33 ·
2
Replies
33
Views
3K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 2 ·
Replies
2
Views
1K
  • · Replies 1 ·
Replies
1
Views
1K
  • · Replies 12 ·
Replies
12
Views
5K
  • · Replies 7 ·
Replies
7
Views
2K
  • · Replies 7 ·
Replies
7
Views
3K