Introduction

What is data analysis and why is it important?

Unlike some professions which may be more qualitative in nature, most engineering professions are quantitative. Consequently, engineers typically deal with a lot of data (values derived from scientific experiments). As was mentioned in Chapter 2, engineers are in the business of building things that turn ordinary people into superhumans. In order to build things in a safe and responsible manner, engineers are obligated to conduct a lot of experiments and collect a lot of data on those experiments. Engineers then use different statistical tools and methods to analyze the data. We will investigate some of these methods in Chapter 5. For this Chapter, we will investigate one of the main tools engineers used to tabulate and interpret data.

Different types of engineers deal with different types of data. For example, a mechanical or civil engineer may have data pertaining to the stress and strain measured in a deforming material. A biomedical engineer may have data on the electrical potential from an electrocardiogram. A chemical engineer may have industrial chemical reactor data that contains dozens of different operating parameters and reaction products. The list goes on but the one thing that is true is that engineers deal with a lot of data. One tool to analyze and review data is Microsoft Excel.

You may have some exposure to Excel; perhaps you had to learn how to use it in high school, you watched your parents use it to keep track of a budget, or you saw a teacher use it to keep track of grades. Whatever your experience level is with Excel, we will spend the next two chapters investigating the capabilities of Excel and what you as an engineer will be expected to be able to accomplish with the software. Before we jump into learning, it is helpful to reflect on what you know about Excel already.

In this chapter, we will explore Microsoft Excel and what we will be expected of you as an engineering student. That means learning: