End-to-end Data Analytics for Product Development

1Basic Statistical Background

1.1 Introduction

Statistics and data analytics play a central role in improving processes and systems and in decision‐making for strategic planning and manufacturing (Roberts, H. V., 1987). During experimental research, statistical tools can allow the experimenter to better organize observations, to specify working hypotheses and possible alternative hypotheses, to collect data efficiently, and to analyze the results and come to some conclusions about the hypotheses made.

This is an introductory chapter where readers can review several basic statistical concepts before moving on to the next chapters. Sixteen sections titled Stat Tools will introduce some key terms and procedures that will be further elaborated and referred to throughout the text.

Specifically, this chapter deals with the following:

Topics	Stat tools
Statistical variables and types of data	1.1
Statistical Units, populations, samples	1.2
Introduction to descriptive and inferential analyses	1.3, 1.12, 1.13
Data distributions	1.4, 1.5
Mean values	1.6, 1.7
Measures of variability	1.8, 1.9, 1.10
Boxplots	1.11
Introduction to confidence intervals	1.14
Introduction to hypothesis testing procedures, including the p‐value approach	1.15, 1.16

Learning Objectives and Outcomes

Upon completion of the review of these basic statistical concepts, you should be able to do the following:

• Recognize and distinguish between different types of variables.
• Distinguish between a population ...