صفحات العروض بالإنجليزية في الوقت الحالي؛ أما الدرس المرتبط بكل عرض فهو بالعربية بالكامل.
كيف تقرأ هذه الصفحات. كل صفحة تبيّن أي أرقامها محسوبة، وأيها مأخوذ من شكل منشور، وأيها توضيحي. وقد أُنتج بعضها بمساعدة الذكاء الاصطناعي وتذكر ذلك على الصفحة نفسها. هي أدوات تعليمية، وليست قياسات لعتاد حقيقي.
التجارب العملية
العروض التفاعلية
Data explorer
من درس ما هو علم الإحصاء؟
Edit a small dataset (or load symmetric, skewed, bimodal and with-outlier presets) and watch the mean, median, mode, standard deviation, five-number summary and the 1.5×IQR outlier rule recompute, with a live histogram and box plot — the mean chases the tail while the median resists.
Probability simulator
من درس ما هو الاحتمال؟
Run a seeded coin or die and watch the running frequency converge to the true probability while the raw count difference drifts the other way; then set a medical test’s prevalence, sensitivity and specificity and read the exact P(disease | +) off a confusion table and a probability tree — a 99% test on a 1% disease is right only about half the time it says yes.
MCMC sampler
من درس الأساليب الحسابية البايزية
Watch a real Metropolis–Hastings and Gibbs sampler converge to a target. Turn the proposal width and see acceptance and mixing trade off — the sample mean and covariance settle onto the true values as the chain runs.
A/B testing simulator
من درس تصميم التجارب
A two-sample A/B experiment: set the control and variant conversion rates and the per-arm size, and read the pooled two-proportion z, the p-value and the unpooled confidence interval for the lift. See the power to detect the lift, the sample size a target power needs, and why peeking at the results early makes a 5% test reject far more than 5% of the time.
Regression influence
من درس تشخيصات الانحدار
Drag points on a scatter plot and watch least squares, the residual and QQ plots, leverage and Cook’s distance all recompute. Two presets share an x value, so their leverage is identical and only their influence differs.
Central Limit Theorem sandbox
من درس نظرية النهاية المركزية
Choose a parent distribution, a sample size and a number of samples, and watch any parent become normal — the course's central claim, drawn rather than asserted.
p-values, power and the two error rates
من درس منطق اختبار الفرضيات
Effect size, sample size and alpha, with the two error rates moving in opposition and the power curve computed live.
Visualization workshop
من درس تمثيل التوزيعات بيانياً
Good charts vs bad charts, made computable: Anscombe’s quartet (four datasets, identical statistics to two decimals, four different shapes), a truncated axis with a live exaggeration factor, and Simpson’s paradox where the pooled slope reverses within groups.
Non-parametric methods
من درس لماذا اللامعلمية؟
Non-parametric methods, made computable: a kernel density estimate with an adjustable bandwidth (and Silverman’s rule) that finds two humps where one fitted normal sees only one; a LOESS smoother that follows a bend the global line flattens; and Spearman’s rank correlation shown against Pearson’s r — rho stays 1 on y = x³ and shrugs off an outlier that drags r.
Time series analysis
من درس أساسيات السلاسل الزمنية
Time-series analysis on a seeded trend + season + noise series: an additive decomposition whose trend, seasonal and residual add back to the series exactly; the ACF and PACF with ±1.96/√N bands, where a seasonal spike stands above the band; and an AR(p) forecast fit by Yule–Walker — for AR(1), φ̂ = ρ₁ exactly.