When will ball 25 drop? Predicting future observations using data

  • Context: High School 
  • Thread starter Thread starter DaveC426913
  • Start date Start date
  • Tags Tags
    Data
Click For Summary
SUMMARY

This discussion focuses on predicting the future observations of billiard balls dropping into a pocket using a dataset of past observations. The user aims to develop an algorithm that estimates when a specific ball, such as ball 25, will drop based on previous drop times. Key insights include the use of sample means for prediction, the importance of selecting appropriate cost functions for accuracy, and the potential for linear regression to improve estimates. The conversation also touches on the challenges of data integrity and the impact of observational biases on predictions.

PREREQUISITES
  • Understanding of basic statistical concepts such as mean and variance.
  • Familiarity with linear regression techniques and their applications.
  • Knowledge of algorithm development for predictive modeling.
  • Experience with data formats like JSON and CSV for data manipulation.
NEXT STEPS
  • Research linear regression methods in Python using libraries like scikit-learn.
  • Explore cost functions in predictive modeling, focusing on least squares and L1 norms.
  • Learn about Bayesian statistics and its application in predictive algorithms.
  • Investigate data cleaning techniques and best practices for maintaining data integrity.
USEFUL FOR

Data scientists, statisticians, and software developers interested in predictive analytics and algorithm design will benefit from this discussion.

  • #31
mfb said:
Sure. Your dataset has "plate 54: date, plate 55: date, plate 57: date, plate 58: date, ...
Right. Which is why you originally introduced a distinct index.

I was treating the array index as the x-axis.
i.e. my values would end up being:
item[23]: CDJ
item[24]: CDK
item[25]: CDM
So, CDL is not there, and therefore no gap where there should be a gap, putting the next item out of line.

For you:
item[23]: {index:23, plate: CDJ}
item[24]: {index:24, plate: CDK}
item[25]: {index:26, plate: CDM}
So the trend is conserved.

I see now.
 
Physics news on Phys.org
  • #32
I think what you may be looking for is Kalman Filter.
 

Similar threads

Replies
2
Views
3K
Replies
2
Views
707
  • · Replies 4 ·
Replies
4
Views
2K
  • · Replies 7 ·
Replies
7
Views
4K
  • · Replies 24 ·
Replies
24
Views
2K
  • · Replies 19 ·
Replies
19
Views
2K
  • · Replies 5 ·
Replies
5
Views
3K
  • · Replies 3 ·
Replies
3
Views
8K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 8 ·
Replies
8
Views
2K