**Author**: Gerhard Bohm

**Publisher:**

**ISBN:**9783935702416

**Size**: 38.99 MB

**Format:**PDF, ePub, Mobi

**Category :**

**Languages :**en

**Pages :**447

**View:**2250

An Introduction to Statistics and Data Analysis Using Stata® by Lisa Daniels and Nicholas Minot provides a step-by-step introduction for statistics, data analysis, or research methods classes with Stata. Concise descriptions emphasize the concepts behind statistics for students rather than the derivations of the formulas. With real-world examples from a variety of disciplines and extensive detail on the commands in Stata, this text provides an integrated approach to research design, statistical analysis, and report writing for social science students.

This introductory statistics textbook conveys the essential concepts and tools needed to develop and nurture statistical thinking. It presents descriptive, inductive and explorative statistical methods and guides the reader through the process of quantitative data analysis. In the experimental sciences and interdisciplinary research, data analysis has become an integral part of any scientific study. Issues such as judging the credibility of data, analyzing the data, evaluating the reliability of the obtained results and finally drawing the correct and appropriate conclusions from the results are vital. The text is primarily intended for undergraduate students in disciplines like business administration, the social sciences, medicine, politics, macroeconomics, etc. It features a wealth of examples, exercises and solutions with computer code in the statistical programming language R as well as supplementary material that will enable the reader to quickly adapt all methods to their own applications.

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.

INTRODUCTION TO STATISTICS AND DATA ANALYSIS, 4th Edition, introduces you to the study of statistics and data analysis by using real data and attention-grabbing examples. The authors guide you through an intuition-based learning process that stresses interpretation and communication of statistical information. Simple notation--including the frequent substitution of words for symbols--helps you grasp concepts and cement your comprehension. You'll also find coverage of the graphing calculator as a problem-solving tool, plus hands-on activities in each chapter that allow you to practice statistics firsthand. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

Take the fear out of statistics with this straightforward, practical and applied book on the ‘how and why’ of using statistics. Introduction to Statistics for Nurses is an essential introductory text for all nursing students coming to statistics for the first time. The nursing profession involves the use of statistics every day, for example in the cases of mortality rates, average life expectancies, percentage recovery rates, average remission times, and the findings of which drugs work best with which illnesses. In fact, all of the policies that surround this job, the treatment strategies, and all the facts described above are derived from the use of statistics. This book will help students to understand the use of statistics in nursing literature, and shows how to use statistics effectively in answering research questions. Case studies throughout show how statistics are applied in nursing research and frequent exercises help to test the reader's knowledge as they progress.

Naive set theory; Probability; Random variables: discrete case; Random variables: continuous and mixed cases; Moments; Sums of random variables and limit laws; An example of statistical analysis; Point estimation and statistical inference principles; Tests of hypotheses; Interval estimation; Ranking and selection procedures; Decision theory; Nonparametric statistical inference; Regression and linear statistical inference.

The introductory statistics course presents serious pedagogical problems to the instructor. For the great majority of students, the course represents the only formal contact with statistical thinking that he or she will have in college. Students come from many different fields of study, and a large number suffer from math anxiety. Thus, an instructor who is willing to settle for some limited objectives will have a much better chance of success than an instructor who aims for a broad exposure to statistics. Many statisticians agree that the primary objective of the introductory statistics course is to introduce students to variability and uncertainty and how to cope with them when drawing inferences from observed data. Addi tionally, the introductory COurse should enable students to handle a limited number of useful statistical techniques. The present text, which is the successor to the author's Introduction to Statistics: A Nonparametric Approach (Houghton Mifflin Company, Boston, 1976), tries to meet these objectives by introducing the student to the ba sic ideas of estimation and hypothesis testing early in the course after a rather brief introduction to data organization and some simple ideas about probability. Estimation and hypothesis testing are discussed in terms of the two-sample problem, which is both conceptually simpler and more realistic than the one-sample problem that customarily serves as the basis for the discussion of statistical inference.

This book explains the statistical concepts and then uses Microsoft Excel functions to illustrate how to get results using the appropriate techniques which will help researchers directly with their research.

Statistics can be difficult, but this revised 3rd edition of Introduction to Statistics in Psychology makes it much easier. Any psychology student, whether at introductory, intermediate or advanced level will find the book a very useful companion to their statistics course.

Introduction to Statistics with SPSS offers an introduction to statistics that can be used before, during or after a course on statistics. Covering a wide range of terms and techniques, including simple and multiple regressions, this book guides the student to enter data from a simple research project into a computer, provide an adequate analysis of the data and present a report on the findings.