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Transform raw data into meaningful insights and discover the foundations of inference
Mean, median, and mode
Spread and dispersion
Shape of your data
The magic of sampling
Descriptive statistics are the foundation of all data analysis. In this chapter, you'll learn the tools to summarize, visualize, and understand data. Then discover how sampling distributions bridge the gap between samples and populations, culminating in the profound Central Limit Theorem.
Data analysis fundamentals
All sections are accessible - follow the numbered sequence for the best learning experience
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Build formulas step-by-step
Build descriptive statistics formulas interactively. Click on each part to understand why it's there and how it works.
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Understanding data summarization
Learn what descriptive statistics are, why we need them, and the types of data we work with.
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Mean, median, and mode
Master the three fundamental measures that describe the center of your data.
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Spread and dispersion
Understand how spread out your data is with range, variance, and standard deviation.
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Visualizing data patterns
Master the essential visualization techniques: histograms, boxplots, scatter plots, and more.
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From samples to populations
Discover how sample statistics behave when we repeatedly sample from a population.
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Statistics' most important result
Experience the magic of the CLT: how sample means become normally distributed regardless of the population.
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t, F, and chi-square distributions
When population parameters are unknown, meet the distributions needed for real-world inference.
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Start with fundamentals to understand the core concepts
Apply concepts to real-world data to reinforce understanding
Learn when and how to apply each concept effectively