Unit 1 of 12

Statistical Thinking and Data

  • 3 lessons
  • Videos 1 to 3

Statistics starts with a question about a group and a clear idea of what each recorded value means. This unit defines populations, samples and variables and looks at the quality of a data table.

A statistic such as a sample mean or proportion describes the observed data, while a parameter describes the whole population, and different samples can give different values of the same statistic. Variables are categorical or numerical and are measured on nominal, ordinal, interval or ratio scales, which decides which calculations make sense. The unit ends with data tables in practice, covering data provenance, duplicates, outliers and missing values, and shows how dropping incomplete rows can change a conclusion.

Every lesson is one video. Each lesson page has the definitions and an example for every key term.

Questions, Variables and Data Quality

  1. Introduction to Statistics

    What makes a question statistical, how a population, a sample and the observational unit are defined, how a parameter differs from a statistic, why statistics vary between samples, and description versus inference.

    Video 1

  2. Types of Data and Measurement

    How to tell categorical from numerical and discrete from continuous variables, what the four levels of measurement allow, and how operational definitions, accuracy, precision, rounding and 0/1 indicators shape conclusions.

    Video 2

  3. Data Tables, Missing Values and Data Quality

    How data provenance, a data dictionary and a data cleaning log keep a table's meaning traceable, and how to handle duplicate records, outliers and missing values, including missingness mechanisms and complete-case analysis.

    Video 3