Foundations of Statistics: Data, Variables and Sampling

Course Introduction and ObjectivesPage 3

This lecture introduces ECON 1005 at the University of the West Indies, Cave Hill Campus. It outlines the course roadmap which progresses from descriptive statistics to probability, random variables, sampling, hypothesis testing, and regression analysis. Key objectives include classifying variables, distinguishing between population parameters and sample statistics, and understanding various data collection methods.

Data, Statistics, and Types of AnalysisPage 9

Statistics is defined as the science of collecting, organizing, analyzing, and interpreting data. Applied statistics is divided into two branches: descriptive statistics, which summarize observed data using tables and graphs, and inferential statistics, which use sample data to estimate or draw conclusions about a broader population.

Anatomy of a DatasetPage 15

A dataset consists of elements (individual units of study), variables (specific characteristics or columns), and observations (complete rows of data). Understanding this structure is essential for accurate statistical analysis.

Classification of VariablesPage 27

Variables are classified as qualitative (categorical) or quantitative (numerical). Quantitative variables are further divided into discrete (countable, such as counts of items) and continuous (measurable on a scale, such as height or time).

Data StructuresPage 34

Data can be categorized by structure: cross-sectional (many elements at one point in time), time-series (one element over multiple points in time), or panel (multiple elements over multiple points in time).

Sampling Methods and ErrorsPage 44

Statistics utilizes samples to infer characteristics about a population (parameters). Common probability sampling methods include simple random, systematic, stratified, and cluster sampling. The lecture highlights the distinction between sampling errors (inherent chance variation) and non-sampling errors (systematic flaws in survey design or data collection).