Ebook Dealing With Statistics What You Need To Know
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EBOOK: Dealing with Statistics: What you need to know
Author: Reva Berman Brown
language: en
Publisher: McGraw-Hill Education (UK)
Release Date: 2007-12-16
‘This is a highly accessible, yet an adequately sophisticated text, which can be enjoyed by students across the skills spectrum. I am confident that it will help students who suffer from maths phobia as it offers to teach statistics with anxiety-busting clarity. The book benefits from easy to follow demonstrations and illustrations of statistical methods and techniques, which are highly relevant for business and management research at the undergraduate and masters level courses.’ Professor Mustafa F. Ozbilgin, University of East Anglia, UK Are you confused about which statistical tests to use, when you should be using them and why you should be using them? This book is about helping you to choose and use the right statistical technique to analyse your data and write about your results and findings convincingly. It provides a concise and accessible guide to the essential statistical skills needed for success in your assignment, project or dissertation. Berman Brown and Saunders concentrate on particular statistical tests and their three Ws – what, why, and when. They provide you with the tools to choose the graphs and statistics that are suitable for your data, and to understand what the statistical results actually mean. In addition, the book: Explains why it is impossible to avoid using statistics in analysing data Describes the language of statistics to make it easier to understand the various terms used for statistical techniques Deals with using tables and charts to present data so that they are easy to understand Explains the statistics used to describe data used to infer differences and relationships. The book also includes a handy alphabet of statistics as well as a glossary of key statistical terms. Dealing with Statistics is key reading for students undertaking a social science or business and management assignment, project or dissertation as part of an undergraduate or Masters qualification.
All of Statistics
Author: Larry Wasserman
language: en
Publisher: Springer Science & Business Media
Release Date: 2013-12-11
Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like non-parametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analysing data.
Introduction to Statistics
Author: Jim Frost
language: en
Publisher: Statistics By Jim Publishing
Release Date: 2020-07-21
Learn statistics without fear! Build a solid foundation in data analysis. Be confident that you understand what your data are telling you and that you can explain the results to others! I'll help you intuitively understand statistics by using simple language and deemphasizing formulas. This guide starts with an overview of statistics and why it is so important. We proceed to essential statistical skills and knowledge about different types of data, relationships, and distributions. Then we move to using inferential statistics to expand human knowledge, how it fits into the scientific method, and how to design and critique experiments. Learn the fundamentals of statistics. Why is the field of statistics so vital in our data-driven society? Interpret graphs and summary statistics. Find relationships between different types of variables. Understand the properties of data distributions. Use measures of central tendency and variability. Interpret correlations and percentiles. Use probability distributions to calculate probabilities. Learn about the normal distribution and the binomial distributions in depth. Grasp the differences between descriptive and inferential statistics. Use data collection methodologies properly and understand sample size considerations. Critique scientific experiments-whether it's your own or another researcher's.