Principles of Managerial Statistics and Data Science

2Concepts in Statistics

2.1 Introduction

The first chapter served as an appetizer by discussing the importance of Statistics and the proper application of statistical methods. It also discussed the need to combine statistical procedures with critical thinking. But we need a deeper understanding of concepts about data, data collection, and statistics.

First things first, data is a collection of facts about multiple units. A person, a car, a company product are examples of what we call units. A particular value or fact of the data is known as an observation. The facts collected are typically described in words or numerical measurements. Each fact is termed informally as a variable. A data set collects several facts from multiple units. For the purpose of statistical analysis, it is best to organize the data set so that each row represents a series of facts on a unit and each column represents a variable.

Example 2.1

Chicago School's data for 2016–2017 is available online.¹ Below, we can see some of the observations from this data set. Some of the variables (e.g. School Type) are facts presented in words, while others (e.g. College Enrollment Rate) are numerical facts. Each row pertains to a school, while each column describes a fact or variable. The entire data set has over 660 rows and 90 columns.

To extract useful information from this data set, we require statistics. Also worth noting is that some of the cells are empty, for example, the first few rows of college enrollment ...