Calculating average from probabilistic measurements?

  • Context: Undergrad 
  • Thread starter Thread starter mkbh_10
  • Start date Start date
  • Tags Tags
    Average Measurements
Click For Summary
SUMMARY

The discussion focuses on calculating the average probability of success from probabilistic measurements derived from repeated experiments. The user conducted 20 sets of 50 trials each, resulting in a total of 1000 trials. Each set produced a probability of success, p, calculated as p=s/n, where s is the number of successes. The user seeks a method to combine the means and standard deviations of two distributions of p values obtained from separate experiments.

PREREQUISITES
  • Understanding of basic probability concepts, including mean and standard deviation.
  • Familiarity with statistical distributions and their properties.
  • Knowledge of experimental design, specifically repeated trials.
  • Experience with statistical software or tools for data analysis, such as R or Python.
NEXT STEPS
  • Learn how to calculate the combined mean and standard deviation of two distributions.
  • Research the concept of weighted averages in statistics.
  • Explore the use of R or Python libraries for statistical analysis, such as NumPy or SciPy.
  • Study the Central Limit Theorem and its implications for combining distributions.
USEFUL FOR

Statisticians, data analysts, researchers conducting experiments, and anyone involved in probabilistic modeling and data interpretation.

mkbh_10
Messages
217
Reaction score
0
I have got a sample size of 1000 and I calculated the mean probability of success of an event by breaking this sample size into sets of 50 and also have the standard deviation and standard error of mean of this success.

Now I repeat this process and have another set of data.

What will be the process of calculating the average of the probability and the error?
 
Last edited:
Physics news on Phys.org
The setup is:
You have done an experiment of n(=50) identical trials which you repeat m(=20) times getting N=nm(=1000) trials.
In each experiment you have s successes, so the probability of a success in each experiment is estimated as: p=s/n or something like that?
This gives you n slightly different values for p - a "distribution" - from which you can find a mean and a standard deviation.

You do this again ... getting another mean and standard deviation from the new distribution of p values.

Now you are wondering how to combine the two distributions?
That about it?
 

Similar threads

  • · Replies 4 ·
Replies
4
Views
3K
  • · Replies 3 ·
Replies
3
Views
3K
  • · Replies 4 ·
Replies
4
Views
2K
  • · Replies 10 ·
Replies
10
Views
3K
  • · Replies 1 ·
Replies
1
Views
1K
  • · Replies 21 ·
Replies
21
Views
3K
  • · Replies 7 ·
Replies
7
Views
3K
  • · Replies 19 ·
Replies
19
Views
8K
  • · Replies 76 ·
3
Replies
76
Views
7K
  • · Replies 28 ·
Replies
28
Views
3K