Statistics for Data Science — Topics Overview

Seven bite-sized topics take you from the definition of statistics through sampling, data organisation, and measurement scales.

1

Introduction to Statistics

Definition, evolution of the field, and the partnership between descriptive and inferential statistics.

Definition History Branches
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2

Populations and Samples

Build intuition about sampling frames, representativeness, and practical sampling methods.

Population Sample Bias
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3

Purpose of Analysis

When to describe, when to infer, and how both support decision making.

Descriptive Inferential Decisions
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4

Data Foundations

Understand what counts as data, why it is collected, and the difference between structured and unstructured formats.

Definition Sources Structure
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5

Organising Data

Create tidy tables, maintain data dictionaries, and enforce quality checks.

Cases Variables Data Dictionary
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6

Types of Data

Differentiate categorical, discrete, and continuous variables and choose suitable visualisations.

Categorical Numerical Time series
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7

Measurement Scales

Apply the four classical scales and recap the entire week with reflection prompts.

Nominal Ordinal Interval & Ratio
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