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Statistics for Data Science

Learn the statistical thinking that underpins every data science workflow: sampling, descriptive analysis, measurement scales, and the vocabulary needed for inference.

Qualifier 📅 12 Weeks 🎯 Intermediate
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Week Completed
7
Topics Covered
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Progress %
Week 1 of 12 completed

📊 Week 1: Foundations of Statistics

📚 Topic Navigation

✅ 7 Topics Available

Navigate through comprehensive statistics topics with detailed explanations and examples.

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📋 Topics Overview

✅ Completed

Statistics introduction, sampling, data foundations, organization, types, and measurement scales.

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📚 Topics in Week 1

1
Introduction to Statistics
Topic 1
2
Populations & Samples
Topic 2
3
Purpose of Analysis
Topic 3
4
Data Foundations
Topic 4
5
Organising Data
Topic 5
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Types of Data
Topic 6
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Measurement Scales
Topic 7
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🎯 Week 1 Summary

This week covers fundamental statistical concepts essential for data science, including the definition of statistics, sampling methods, data organization, data types, and measurement scales.

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Week 2: Probability Fundamentals

Coming soon! We will cover probability rules, conditional probability, and intuition-building experiments.

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Week 3: Probability Distributions

Coming soon! We will explore discrete and continuous distributions used throughout data science.

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Week 4: Sampling and Estimation

Coming soon! Sampling distributions, estimators, and confidence intervals will take centre stage.