# Introduction

## Description of the Lesson

This starting week you will be familiarized with the basic definitions of statistics and probability, and more importantly, you will understand the importance of statistics to assess problems in forensic science. A case scenario involving different types of physical evidence will be introduced. Uncertainties related to the different elements of the case scenario will be shown. You will also be introduced to the R software, which will be used during this course for the basic statistical operations as well as for the generation of graphs.

## Objectives of the Lesson

1. Introduction - Review syllabus

2. Understand the fundamental need for statistics in forensic science to handle uncertainty in scientific evidence

3. Learn basic definitions of statistics and probability

4. Learn the main reasoning mechanisms

5. Correctly install R software on the computer

## What Elements of the Scenario are we Addressing in this Lesson?

In this introductory part, general aspects of the scenario are considered. We essentially introduce the case and show how statistics play an important role for evaluating the uncertainties surrounding the investigated case. More specifically:

- We tackle the approach followed during the crime scene investigation, in this case to emphasize that the generation of physical evidence at the scene is circumstantial and not planned;
- Examples of fingerprints and glass evidence are used to show difference between descriptive statistics and inferential statistics;
- An example of a DNA locus is used to describe the structure of a dataset;
- The contribution of latent prints to our case is used to introduce the concept of conditional probabilities;
- We tackle the approach followed during the crime scene investigation in this case to distinguish and illustrate deductive, inductive and abductive reasoning.