Unsure Calculator is a simple web-based calculator that handles uncertain inputs. Instead of precise numbers, users input estimated ranges (e.g., "100 to 200") or distributions (e.g., "normal(100, 10)"). The calculator then performs the requested arithmetic operations (add, subtract, multiply, divide) and displays the resulting probability distribution of possible outcomes, visualized as a histogram. This allows users to quickly see the range and likelihood of different outcomes when dealing with imprecise estimations, making it useful for back-of-the-napkin calculations involving uncertainty.
Napkin Math Tool is a web-based calculator designed for quick, back-of-the-envelope estimations and explorations. It emphasizes natural language input, allowing users to type expressions like "2 apples + 3 oranges" or "10% of 1 million." It handles unit conversions, uncertainties (e.g., "10±1"), and supports variables for building more complex calculations. The tool aims to be a versatile scratchpad for thinking through quantitative problems, offering a more flexible and expressive alternative to traditional calculators.
Hacker News users generally praised the Napkin Math Tool for its simplicity and ease of use, finding it a handy alternative to a full spreadsheet program for quick calculations. Several commenters appreciated the clean interface and the focus on keyboard navigation. Some suggested improvements, such as the ability to copy calculated results, a dark mode, and support for variables and functions. One user pointed out the potential benefit for teaching basic math principles, while another highlighted its usefulness for estimating cloud computing costs. There was also a discussion comparing it to other similar tools like Tydlig and Soulver.
This paper presents a simplified derivation of the Kalman filter, focusing on intuitive understanding. It begins by establishing the goal: to estimate the state of a system based on noisy measurements. The core idea is to combine two pieces of information: a prediction of the state based on a model of the system's dynamics, and a measurement of the state. These are weighted based on their respective uncertainties (covariances). The Kalman filter elegantly calculates the optimal blend, minimizing the variance of the resulting estimate. It does this recursively, updating the state estimate and its uncertainty with each new measurement, making it ideal for real-time applications. The paper derives the key Kalman filter equations step-by-step, emphasizing the underlying logic and avoiding complex matrix manipulations.
HN users generally praised the linked paper for its clear and intuitive explanation of the Kalman filter. Several commenters highlighted the value of the paper's geometric approach and its focus on the underlying principles, making it easier to grasp than other resources. One user pointed out a potential typo in the noise variance notation. Another appreciated the connection made to recursive least squares, providing further context and understanding. Overall, the comments reflect a positive reception of the paper as a valuable resource for learning about Kalman filters.
Summary of Comments ( 134 )
https://news.ycombinator.com/item?id=43690289
HN users generally praised the Unsure Calculator for its intuitive approach to dealing with uncertainty in calculations. Several commenters highlighted its potential usefulness in various fields, from project management and cost estimation to personal finance and everyday decision-making. Some suggested improvements, like adding support for distributions beyond normal distributions, and integration with other tools. The clean UI and ease of use were also commended, though one user pointed out a potential ambiguity in the syntax. The developer engaged with the comments, responding to suggestions and clarifying usage. A few commenters also discussed broader implications of embracing uncertainty in calculations and the importance of tools like this for better decision-making.
The Hacker News post discussing the "Unsure Calculator" has generated a fair number of comments, exploring various aspects and potential improvements of the tool.
Several commenters appreciate the simplicity and user-friendliness of the calculator, praising its intuitive syntax and ease of use for quick, probabilistic calculations. They find the ability to express uncertainty directly within calculations particularly helpful. One commenter even suggests integrating it into a spreadsheet environment, highlighting its potential for broader application.
A common thread among the comments involves discussing alternative approaches and existing tools for similar probabilistic computations. Commenters mention libraries like
uncertaintiesin Python and point to existing Monte Carlo simulation techniques as more robust solutions for complex scenarios. They acknowledge the Unsure Calculator's niche as a lightweight tool for simpler estimations, contrasting it with the more comprehensive functionalities of established libraries.The discussion also delves into the specific implementation details of the calculator, including the choice of the PERT distribution for representing uncertainty. Some commenters question this choice and propose alternative distributions or methods for defining uncertainty ranges. A detailed discussion ensues regarding the implications of using different distributions and their impact on the final results.
Furthermore, commenters explore potential improvements and extensions to the calculator's functionality. Suggestions include adding support for correlations between variables, implementing different aggregation methods, and providing more visualizations for the probability distributions. The possibility of incorporating unit handling and error propagation analysis is also raised.
Finally, a few comments focus on the user interface and user experience, proposing enhancements like improved display of results, better handling of edge cases, and more comprehensive documentation. The overall sentiment is positive, with commenters recognizing the value of the Unsure Calculator as a convenient tool for simple probabilistic estimations while acknowledging the potential for further development and refinement.