A paragraph from the books "Collaborative Statistics" and "Introductory Statistics", available below:

"You are probably asking yourself the question, “When and where will I use statistics?” If you read any newspaper, watch television, or use the Internet, you will see statistical information. There are statistics about crime, sports, education, politics, and real estate. Typically, when you read a newspaper article or watch a television news program, you are given sample information. With this information, you may make a decision about the correctness of a statement, claim, or “fact.” Statistical methods can help you make the “best educated guess.”"

"Statistics is the discipline that concerns the collection, organization, analysis, interpretation, and presentation of data. In applying statistics to a scientific, industrial, or social problem, it is conventional to begin with a statistical population or a statistical model to be studied. Populations can be diverse groups of people or objects such as "all people living in a country" or "every atom composing a crystal". Statistics deals with every aspect of data, including the planning of data collection in terms of the design of surveys and experiments."

(from Wikipedia)

A 16-pages note on simple statistical concepts:

Biography of the authors of the book "Beginning Statistics":

"Douglas Shafer is Professor of Mathematics at the University of North Carolina at Charlotte. In addition to his position in Charlotte he has held visiting positions at the University of Missouri at Columbia and Montana State University and a Senior Fulbright Fellowship in Belgium. He teaches a range of mathematics courses as well as introductory statistics. In addition to journal articles and this statistics textbook, he has co-authored with V. G. Romanovski (Maribor, Slovenia) a graduate textbook in his research specialty. He earned a PhD in mathematics at the University of North Carolina at Chapel Hill."

"Zhiyi Zhang is Professor of Mathematics at the University of North Carolina at Charlotte. In addition to his teaching and research duties at the university, he consults actively to industries and governments on a wide range of statistical issues. His research activities in statistics have been supported by National Science Foundation, U.S. Environmental Protection Agency, Office of Naval Research, and National Institute of Health. He earned a PhD in statistics at Rutgers University in New Jersey."

A textbook titled "Inferential Statistics and Probability - A Holistic Approach" by Professor Maurice Geraghty. The author defines "holistic" as follows:

"Holistic or Eastern tradition analysis is less concerned with the component parts of a problem, mechanism or phenomenon but rather with how this system operates as a whole, including its surrounding environment. For example, a holistic nutritionist would look at the potato in its environment: when it was eaten, with what other foods it was eaten, how it was grown, or how it was prepared. In holism, the potato is much more than the sum of its parts."

Inferential Statistics and Probability - A Holistic Approach

A separate approach is used in the textbook "Foundations in Statistical Reasoning" by Pete Kaslik:

"Since this is an open-resource text and since there are many statistics texts on the market, it would not make sense to invest time and energy on something that can easily be obtained with much less effort. However, because I wanted a textbook that presented statistics the way I like to teach it, and that approach is significantly different from what is presented in traditional textbooks, I wrote this one.

So how does this differ from traditional books? It starts by presenting an overview of the statistical thought process. By the end of chapter 1, students are already familiar with concepts such as hypotheses, level of significance, p-values, errors. Normally these topics are not introduced until after a discussion of probability and sampling distributions. My approach to probability and sampling distributions is also very different. Because students using this book know about hypotheses before we reach the probability section, inferential theory can be developed by applying the probability rules to the testing of a hypothesis. To me, this leads to better and more interesting questions than are typically asked in these sections and gives meaning to these concepts. Other differences include homework problems that require the integration of topics from different chapters as well as one problem in each chapter based on issues discussed in other classes on our campus (e.g. psychology, criminal justice, economics, etc)."

Foundations in Statistical Reasoning

Biography of the lead author of the book "Collaborative Statistics":

"Dr. Illowsky is a Professor of Mathematics & Statistics at De Anza College.

- Doctor of Philosophy in Education 2007, Capella University (Specialization: Instructional Design for Online Learning)

- Master of Arts in Statistics 1983, The Wharton School, University of Pennsylvania (Concentration: Operations Research)

- Bachelor of Science in Mathematics 1981, University at Albany, State University of New York ( Minors: Computer Science, French)"

Below is a similar version of the above book prepared by OpenStax College: