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العربية

مبتدئ · مجانية

Practical Statistics for Everyday Decisions

Turn spreadsheets of orders, surveys, and tickets into confident, data-backed decisions.

موجّهة إلى: analysts, marketers, and managers who work in Excel and want to make decisions from data with confidence..

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Describing and Understanding Data شاهد هذا الجزء على يوتيوب

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درس واحد
  1. Welcome to the course: what you will learn مرحبًا 5 دقائق

الوحدة 1: Data Foundations with Pandas

6 دروس
  1. Track overview: Describing and Understanding Data مقدمة 5 دقائق
  2. Why statistics matters for everyday decisions: from gut feel to numbers الدرس 1 8 دقائق
  3. Loading and inspecting data: pandas DataFrames for order and survey data الدرس 2 9 دقائق
  4. Cleaning messy data: missing values, duplicates, and data types الدرس 3 10 دقائق
  5. Grouping and summarizing: pandas groupby for quick business answers الدرس 4 11 دقيقة
  6. Project: build a clean orders dataset and answer three business questions الدرس 5 11 دقيقة

الوحدة 2: Describing Data: Center and Spread

5 دروس · قريبًا
  1. Mean, median, and mode: which average tells the truth الدرس 1 قريبًا
  2. Spread: range, variance, and standard deviation explained simply الدرس 2 قريبًا
  3. Percentiles and quartiles: finding typical and extreme values الدرس 3 قريبًا
  4. Box plots: spotting outliers and comparing groups at a glance الدرس 4 قريبًا
  5. Project: describe support ticket resolution times and flag outliers الدرس 5 قريبًا

الوحدة 3: Visualizing Distributions

5 دروس · قريبًا
  1. Histograms: seeing the shape of your data with matplotlib الدرس 1 قريبًا
  2. Skewness and shape: symmetric, left-skewed, right-skewed data الدرس 2 قريبًا
  3. Comparing distributions across groups: overlays and small multiples الدرس 3 قريبًا
  4. Choosing the right chart: histogram vs box plot vs bar chart الدرس 4 قريبًا
  5. Project: compare order values across customer segments visually الدرس 5 قريبًا

الوحدة 4: Probability and Distributions in Plain Words

5 دروس · قريبًا
  1. Probability basics: chances, odds, and everyday misunderstandings الدرس 1 قريبًا
  2. The normal distribution: the bell curve and the 68-95-99.7 rule الدرس 2 قريبًا
  3. The binomial distribution: counting successes in repeated trials الدرس 3 قريبًا
  4. Expected value: what it means and how to compute it in Python الدرس 4 قريبًا
  5. Project: estimate expected revenue from a promotion using probability الدرس 5 قريبًا

Testing Ideas and Finding Relationships شاهد هذا الجزء على يوتيوب

الوحدة 5: Sampling and Uncertainty

6 دروس · قريبًا
  1. Track overview: Testing Ideas and Finding Relationships مقدمة قريبًا
  2. Populations vs samples: why we can't survey everyone الدرس 1 قريبًا
  3. Why samples vary: sampling error and the sampling distribution الدرس 2 قريبًا
  4. The Central Limit Theorem in plain words, with a simulation الدرس 3 قريبًا
  5. Confidence intervals: how sure are we about an estimate الدرس 4 قريبًا
  6. Project: estimate average order value with a confidence interval الدرس 5 قريبًا

الوحدة 6: Hypothesis Testing Without Fear

5 دروس · قريبًا
  1. What a hypothesis test actually does: null, alternative, and logic الدرس 1 قريبًا
  2. P-values explained: what they do and don't mean الدرس 2 قريبًا
  3. Common traps: p-hacking, multiple testing, and misreading significance الدرس 3 قريبًا
  4. One-sample and two-sample t-tests in Python الدرس 4 قريبًا
  5. Project: test whether a new checkout page changed average order value الدرس 5 قريبًا

الوحدة 7: A/B Testing in Practice

5 دروس · قريبًا
  1. Designing a fair A/B test: randomization and sample size الدرس 1 قريبًا
  2. Testing conversion rates: proportions and the chi-square test الدرس 2 قريبًا
  3. Reading A/B test results: effect size, confidence, and business impact الدرس 3 قريبًا
  4. When A/B tests mislead: peeking early, novelty effects, and seasonality الدرس 4 قريبًا
  5. Project: analyze a website A/B test and recommend a decision الدرس 5 قريبًا

الوحدة 8: Relationships: Correlation and Regression

5 دروس · قريبًا
  1. Correlation: measuring how two variables move together الدرس 1 قريبًا
  2. Correlation is not causation: classic traps and how to spot them الدرس 2 قريبًا
  3. Simple linear regression: fitting a line to explain a relationship الدرس 3 قريبًا
  4. Interpreting regression output: slope, intercept, and R-squared الدرس 4 قريبًا
  5. Project: predict support ticket volume from orders and decide staffing الدرس 5 قريبًا