Statistics AI: Math Solver

Your Personal AI Statistics Tutor — Solve Any Stats Problem with a Photo

Struggling with statistics homework or preparing for exams? Stats AI is a complete learning companion that combines AI-powered problem solving with interactive tutoring and practice tools.

Solve Statistics Problems Instantly

Photo Recognition Technology
Snap a photo of any statistics problem, handwritten or printed, and get clear step-by-step solutions. The AI recognizes:
• Probability distributions and calculations
• Hypothesis testing (t-tests, z-tests, chi-square)
• Regression analysis (linear, multiple, logistic)
• ANOVA and experimental design
• Descriptive statistics and data visualization
• Confidence intervals and sampling methods

Interactive AI Chat
Ask follow-up questions such as:
• Why was a t-test used instead of a z-test?
• What assumptions are needed for ANOVA?
• Can you explain this step differently?

Get explanations tailored to your understanding.

Learn Through Practice and Gamified Learning

Interactive Quizzes
Test your understanding with quizzes on key topics. Track your progress across descriptive and inferential statistics.

Smart Flashcards
Review formulas, definitions, and concepts with AI-generated flashcards designed for quick revision.

Problem Library
Browse a collection of solved statistics problems organized by topic and difficulty. Learn by example and explore alternative solution methods.

Progress and Motivation
• Earn points for solving problems and quizzes
• Unlock achievements as you advance
• View analytics of your learning progress
• Maintain streaks to build consistent study habits

Comprehensive Topic Coverage

• Descriptive Statistics – mean, median, mode, standard deviation, variance, IQR
• Probability – basic probability, conditional probability, Bayes' theorem
• Distributions – normal, binomial, Poisson, t-distribution, chi-square
• Hypothesis Testing – one-sample, two-sample, paired t-tests, z-tests
• Regression – linear, multiple, correlation analysis
• ANOVA – one-way, two-way, factorial designs
• Chi-Square Tests – goodness of fit, test of independence
• Confidence Intervals – for means, proportions, differences
• Sampling – methods, central limit theorem, sampling distributions
• Non-Parametric Tests – Mann-Whitney, Kruskal-Wallis, Wilcoxon

Suitable For

• High Sc