What are good books on data analysis
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References from former tutors
Former tutors have compiled a small selection of interesting and helpful literature on statistical data analysis as well as references to a few selected books on the subject of learning styles and learning strategies. Let yourself be inspired and infected by the desire to read about statistical concepts and facts.
Lindenberg, Andreas, Wagner, Irmgard, Fejes Peter 2007: Statistics macchiato. Cartoon stochastics course for schoolchildren and students. Munich: Pearson studies
Statistics macchiato is a book that aims to impart basic knowledge of statistics. It uses comic sequences as well as simple and well-known examples from school and everyday life. However, it does not claim to replace a textbook for students. Rather, it is suitable for refreshing school knowledge and getting an overview of some of the topics discussed in Statistics I. Above all, the summaries at the end of each chapter and the overview at the end of the book offer the opportunity to briefly recall the material. The focus of the book is clearly on the calculation of probability, but the chapters on binomial and normal distribution as well as the hypothesis test can also help in understanding the course. Statistics macchiato also gives you a first look at Statistics II.
The problems of the topics covered are presented in an understandable way and supplemented or clarified by comics. Thus, the material is conveyed in a more relaxed way, instead of using the theoretical approach familiar from other textbooks. Statistics macchiato also offers the opportunity to deepen what you have learned in a “practical part”. The solutions to the corresponding tasks, as well as further information, for example for statistical work with Excel, can be called up on the Internet. In summary, it can be said that statistics macchiato does not cover all the subject areas of Statistics I, but it is well suited to repeat and to recall some things.
(by Friederike Rüppel)
Benningshaus, Hans 2007: DeskRiptive Statistics - An Introduction for Social Scientists. VS Published by Wiesbaden.
The book: "Descriptive Statistics - An Introduction for Social Scientists" by Hans Benninghaus is a classic textbook that contains all the basic terms for descriptive statistics. I have had very good experiences with this book. Especially at the very beginning it was important for me to look up the terms that I heard in the lecture. The order of the topics is not identical to the lecture, but everything important about descriptive statistics can be found in the table of contents. Most of the topics discussed in the lecture can be looked up here. The book is very well structured and easy to understand. A lot of work is done with illustrative examples from the social sciences, so the book is particularly suitable for students of sociology.
The contents of the book go beyond what was discussed in the lecture. Especially in the back part you come across terms that are relevant for Statistics II.
It was very pleasant for me that all the formulas could be found in the book exactly as they were on the slides in the lecture. The graphical representations and tables are also very clear and understandable. Regarding the content, it should also be noted that the calculation of probability is not dealt with in this book. Additional literature is available on this topic, such as the book: "Statistics macchiato".
In summary, I can say that I was very happy with this book. Especially for self-study and for support at the beginning. Because when I initially felt a bit unsure of how to use basic statistical terms, this book could really help me.
(by Ulrike Schaumburg)
Diaz-Bone, Rainer, 2006: Statistics for Sociologists. UTB basics UVK publishing company
In my opinion, statistics for sociologists are a good book to prepare for the exam or to reactivate your own knowledge. You will come across statistics again later. However, I think it is not necessarily suitable for accompanying lectures because it has its own structure that is not always congruent with that of the lecture.
The book provides in-depth insights into statistics relevant to the social sciences and also grants insights into the fundamentals and most common methods of empirical social research.
It should be noted, however, that, in my opinion, it is not necessarily suitable as a "reference work", as not every single calculation method is explained from the ground up in every chapter. The chapters of the book build on each other and require an understanding of the previous ones in later explanations.
However, this understanding is certainly promoted by the way the content is conveyed. Although formulas and technical terms are used, these are derived or explained at the beginning of the corresponding chapter.
In some cases, some arithmetic operations are only explained in a very abstract way or only explained verbally without an arithmetic example. In and of itself, however, the book often works with graphics and descriptive examples and enables a good familiarization.
In summary, it can be said that the book is certainly very suitable for repeating and reactivating knowledge, these qualities therefore, in my opinion, characterize it as certainly suitable for exam preparation. It is also suitable for those people who find it easy or who prefer to work their way into a book and prefer a personal intensification of the content. Those who are looking for a reference work or exercises should perhaps look around for another book.
Nevertheless, it is always worth taking a look at the book and your own judgment is of course always more reliable than that of someone else.
(by Floris Bernhardt)
Müller-Benedict, Volker, 2006: Basic course in statistics in the social sciences. VS Verlag.
This book provides a compact overview of the basics of statistics. The definitions are clearly highlighted, the explanations are to the point and offer realistic examples. They offer a high level of credibility by using suitable data from social science data collections, among other things. It can happen that an example is unnecessarily cryptic (e.g. 1000+ cases in the median). However, this rarely happens, but it is still understandable.
Zöfel, Peter, 2000: Understanding Statistics. Munich: Adison-Wesley.
Peter Zöfel fills his book "Understanding Statistics" with the important procedures and measurements as well as with many additional, advanced topics. The examples are all realistic and helpful. There is enough space for graphics and tables. In addition to the extra chapter on statistics software, the reference to digital implementations when dealing with data runs through the entire book. The many topics that go beyond the lecture offer further insights, but can also be confusing. When repeating the basics, a more compact overview is quickly missing.
(by Robert Skok)
Oestreich, Markus; Romberg, Oliver, 2009: Don't panic about statistics. Success and fun in the horror subject of non-technical courses. Wiesbaden: Vieweg + Teubner
With this book you notice the "unusual" tone with the reader right from the start. It is noticeable that one is addressed with "you", which is rather irritating at first, as it is very unusual. The general writing style is also kept very relaxed and “youthful”, which in my opinion seems rather silly for a scientific book.
In some places one notices an ironic undertone, which reinforces the view of the statistics rather negatively. However, the graphics and tables, especially for the summary at the end of a chapter, are very clear and helpful to get an overview of the topic.
The examples used are very close to everyday life, which makes them easier to remember.
(by Anna Graser)
Learning aids and books on learning strategies
Cottrell, Stella, 2010: Studying - the handbook. Heidelberg: spectrum.
This handbook, which was developed in practical collaboration with students over a period of 20 years, contains valuable tips and instructions for “learning to learn” during studies. It covers all conceivable areas of the study process, from self-assessment to time, project and stress management, research and reading skills to confident handling of numbers and writing your own texts, and is primarily designed for beginners and first-year students. Among other things, the study guide contains helpful templates for self-assessment, checklists, strategy planners and evaluation sheets that can be copied for personal use.
Mandl, Heinz and Helmut Felix Friedrich (Ed.), 2006: Handbuch Lernstrategien. Göttingen: Hogrefe.
This book provides information about different types of learning strategies and the corresponding current state of research. Both cognitive and metacognitive strategies are listed, strategies of using knowledge and influencing learning-related motivation and emotions as well as those of cooperative learning and resource use are highlighted. In addition to the extensive range of theoretically processed organizational and elaboration strategies, the volume also includes more specific chapters on learning during studies or self-directed learning.
Arnold, Ellen, 2000: Now I understand! Better learning outcomes by promoting different types of learners. Mühlheim an der Ruhr: Verlag an der Ruhr.
In this guide book, which is primarily intended as an aid to supervisors, teachers and parents, various types of learner and their respective preferences when learning new topics are presented. Even if the contents are mainly tailored to the target group of students, they can also serve to gain an overview of the breadth of the field of learning strategies during the course of study and, above all, provide suggestions for one's own way of learning and the to reflect the applied learning strategy in relation to the personal learning type.
Leopold, Claudia, 2009: Learning strategies and text comprehension. Münster: Waxmann.
This very theoretically oriented book is aimed at the target group of educators and against this background gives an overview of the different psychological concepts on the subject of learning strategies and what their advantages and disadvantages are in promoting learning. The results of empirical research on learning strategies and text comprehension are used to derive the relationship between the use of a specific learning strategy and the learning success achieved.
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