Quantitative Techniques I

Descriptive Statistics, Probability, and Index Numbers

An open undergraduate textbook for Quantitative Techniques I (Técnicas Cuantitativas I) at the University of Granada. Consolidates lecture notes, R labs, and interactive self-assessments into a single reproducible volume covering descriptive statistics, probability, random variables, discrete distributions, index numbers, and descriptive time-series analysis.

Author

Alessio Gaggero

Published

May 20, 2026

Preface

Quantitative Techniques I — Descriptive Statistics, Probability, and Index Numbers is the open companion textbook for the Técnicas Cuantitativas I course at the University of Granada (UGR), Faculty of Economics and Business Studies. It consolidates lecture notes, R labs, and interactive self-assessments — developed across multiple cohorts — into a single reproducible volume.

0.1 What this book is

A unified first-year undergraduate text that walks the reader from raw observations to a working command of classical descriptive statistics, probability, the most common discrete distributions, index numbers, and descriptive time-series analysis. The course deliberately precedes inferential statistics and econometrics: there are no hypothesis tests, no confidence intervals, and no sampling-distribution machinery here. Those tools belong to the second-semester sequel and to Econometrics I.

Each chapter follows the same six-section template:

Learning outcomes
Motivating empirical question
Theory
R Lab — worked example in R
Self-check — interactive multiple-choice quiz
Exercises (★ easy, ★★ medium, ★★★ analytical)

0.2 How this book is organised

Chapter	Topic
1	Univariate Descriptive Statistics
2	Bivariate Descriptive Statistics
3	Introduction to Probability
4	Random Variables
5	Discrete Probability Distributions
6	Index Numbers
7	Time Series (descriptive)
App. A	Mathematical and Combinatorial Prerequisites
App. B	Statistical Reference Tables
App. C	Formula Sheet and Exam Preparation

0.3 Editions and license

This book is released under a Creative Commons Attribution 4.0 International (CC BY 4.0) license. It is monolingual English at v1.0. A Spanish edition may follow in a future release; the project scaffolding is structured to make that addition straightforward.

0.4 How to use the source materials

The textbook is built with Quarto. Each chapter is a .qmd file that combines prose, executable R code, and self-assessment callouts. To rebuild the book locally from the en/ directory:

quarto render

0.5 Required R packages

install.packages(c("knitr", "rmarkdown", "readxl", "dplyr", "ggplot2", "learnr"))

No external dataset package is required — all examples either simulate data inline (with set.seed(2026)) or read small files included with the project.

0.6 Acknowledgements

UGR Department of Methods of Quantitative Analysis for Economics and Business; the students of multiple cohorts whose questions shaped this text; and the authors of Statistics for Business and Economics (Newbold, Carlson, and Thorne) and Análisis de datos multivariantes (Daniel Peña) on whose pedagogical traditions this book builds.

--- title: "Preface" --- # Preface {.unnumbered} > *Quantitative Techniques I — Descriptive Statistics, Probability, and Index Numbers* is the open companion textbook for the **Técnicas Cuantitativas I** course at the University of Granada (UGR), Faculty of Economics and Business Studies. It consolidates lecture notes, R labs, and interactive self-assessments — developed across multiple cohorts — into a single reproducible volume. ## What this book is A unified first-year undergraduate text that walks the reader from raw observations to a working command of classical descriptive statistics, probability, the most common discrete distributions, index numbers, and descriptive time-series analysis. The course deliberately precedes inferential statistics and econometrics: there are no hypothesis tests, no confidence intervals, and no sampling-distribution machinery here. Those tools belong to the second-semester sequel and to Econometrics I. Each chapter follows the same six-section template: 1. **Learning outcomes** 2. **Motivating empirical question** 3. **Theory** 4. **R Lab** — worked example in R 5. **Self-check** — interactive multiple-choice quiz 6. **Exercises** (★ easy, ★★ medium, ★★★ analytical) ## How this book is organised | Chapter | Topic | |---|---| | 1 | Univariate Descriptive Statistics | | 2 | Bivariate Descriptive Statistics | | 3 | Introduction to Probability | | 4 | Random Variables | | 5 | Discrete Probability Distributions | | 6 | Index Numbers | | 7 | Time Series (descriptive) | | App. A | Mathematical and Combinatorial Prerequisites | | App. B | Statistical Reference Tables | | App. C | Formula Sheet and Exam Preparation | ## Editions and license This book is released under a **Creative Commons Attribution 4.0 International (CC BY 4.0)** license. It is monolingual English at v1.0. A Spanish edition may follow in a future release; the project scaffolding is structured to make that addition straightforward. ## How to use the source materials The textbook is built with [Quarto](https://quarto.org). Each chapter is a `.qmd` file that combines prose, executable R code, and self-assessment callouts. To rebuild the book locally from the `en/` directory: ```bash quarto render ``` ## Required R packages ```r install.packages(c("knitr", "rmarkdown", "readxl", "dplyr", "ggplot2", "learnr")) ``` No external dataset package is required — all examples either simulate data inline (with `set.seed(2026)`) or read small files included with the project. ## Acknowledgements UGR Department of Methods of Quantitative Analysis for Economics and Business; the students of multiple cohorts whose questions shaped this text; and the authors of *Statistics for Business and Economics* (Newbold, Carlson, and Thorne) and *Análisis de datos multivariantes* (Daniel Peña) on whose pedagogical traditions this book builds.