AlgoSpark vs Probability Practice

“AlgoSpark” is an app that participated in the 2025 Swift Student Challenge, but unfortunately, it didn’t win. “AlgoSpark”是一款2025 Swift Student Challenge参赛App，但很遗憾的是，此APP并未获奖。 “AlgoSpark” offers various algorithm courses, including “Introduction to Algorithms,” “Programming Structures,” “Sorting Algorithms,” “Searching Algorithms,” and more. These cover both fundamental and classic computer algorithms. “AlgoSpark”为您准备了多种计算机算法课程，包括“认识算法”、“程序结构”、“排序算法”、“搜索算法”等等计算机基础与经典的算法。 Once you complete all the courses, you’ll earn your very own “Algorithm Trophy”! 当你完成所有算法课程之后，你可以获得一个专属于你自己的“算法奖杯”！ Github: https://github.com/abc2754667876/AlgoSpark

Probability Practice is an educational application designed to help students understand and practice probability concepts through structured quizzes and mock tests. The app provides topic-wise questions covering fundamental and advanced probability topics commonly studied in mathematics and statistics courses. Students can practice conceptual questions, solve numerical problems, and monitor their performance using statistics. The app supports independent learning and systematic revision of probability concepts. Topics Included 1. Basic Concepts of Probability Random experiments, sample space, events, simple and compound events, and equally likely outcomes. 2. Types of Events Mutually exclusive events, exhaustive events, complementary events, independent and dependent events, and equally probable events. 3. Classical Probability Classical probability definition, probability value range, certain and impossible events, complement rule, and basic probability problems. 4. Addition Theorem of Probability Addition rule, mutually exclusive events, general addition theorem, union and intersection of events, and related problems. 5. Conditional Probability Definition of conditional probability, conditional probability formula, dependent and independent events, multiplication rule, and problem solving. 6. Bayes’ Theorem Concept of Bayes’ theorem, prior and posterior probabilities, likelihood, total probability rule, and applications. 7. Random Variables Definition of random variables, discrete and continuous random variables, probability distributions, probability mass functions, and probability density functions. 8. Mathematical Expectation Expected value, properties of expectation, variance, standard deviation, and expectation-related problems. 9. Probability Distributions Bernoulli trials, binomial distribution, mean and variance of binomial distribution, Poisson distribution, and distribution-based numerical problems. 10. Applications of Probability Applications in games, statistics, risk analysis, reliability analysis, decision theory, and real-life situations. Key Features Topic-wise probability practice quizzes Mock tests for overall assessment Daily quiz for regular practice Performance statistics to track progress Structured topics for systematic learning Simple and distraction-free interface Probability Practice is suitable for students studying probability in mathematics, statistics, and related fields who want structured practice and regular revision.