"The book is divided into three Parts: Part One has chapters that introduce data analysis and SPSS; Part Two contains eight chapters on descriptive statistics that begin with frequency tables and go through multiple regression; and Part Three includes six chapters on inferential statistics. Part One: Getting Started begins by answering some questions most students have right at the start © questions like why study data analysis and how much math and computer knowledge is required? Essential concepts from research methods relevant for data analysis are also explained. Part Two: Descriptive Statistics: Answering Questions about Your Data demonstrates procedures to use when the analyst is only concerned with describing the cases for which he or she actually has data. Statistics summarizing single variables (univariate statistics) are presented first and then statistics summarizing relationships between variables (multivariate statistics). Frequency tables, measures of central tendency, measures of dispersion, crosstabs, measures of association, subgroup means, and regression are all covered as are bar charts, pie charts, histograms, and clustered bar charts. Part Three: Inferential Statistics: Answering Questions about Populations explains procedures which allow the analyst to draw conclusions about the population from which his or her sample of cases was randomly selected. It begins with a simple chapter on the statistical theory behind inferential statistics. A four-step approach to hypothesis testing is introduced in the next chapter and demonstrated with one-sample t test hypotheses. The remaining chapters present different types of hypothesis tests including paired-samples, independent-samples, one and two-way ANOVA, and chi-square"--Provided by publisher.

A friendly and accessible approach to applying statistics in the real world With an emphasis on critical thinking, The Art of Data Analysis: How to Answer Almost Any Question Using Basic Statistics presents fun and unique examples, guides readers through the entire data collection and analysis process, and introduces basic statistical concepts along the way. Leaving proofs and complicated mathematics behind, the author portrays the more engaging side of statistics and emphasizes its role as a problem-solving tool. In addition, light-hearted case studies illustrate the application of statistics to real data analyses, highlighting the strengths and weaknesses of commonly used techniques. Written for the growing academic and industrial population that uses statistics in everyday life, The Art of Data Analysis: How to Answer Almost Any Question Using Basic Statistics highlights important issues that often arise when collecting and sifting through data. Featured concepts include: • Descriptive statistics • Analysis of variance • Probability and sample distributions • Confidence intervals • Hypothesis tests • Regression • Statistical correlation • Data collection • Statistical analysis with graphs Fun and inviting from beginning to end, The Art of Data Analysis is an ideal book for students as well as managers and researchers in industry, medicine, or government who face statistical questions and are in need of an intuitive understanding of basic statistical reasoning.

Never HIGHLIGHT a Book Again! Includes all testable terms, concepts, persons, places, and events. Cram101 Just the FACTS101 studyguides gives all of the outlines, highlights, and quizzes for your textbook with optional online comprehensive practice tests. Only Cram101 is Textbook Specific. Accompanies: 9781412991322. This item is printed on demand.

In an increasingly data-driven world, it is more important than ever for students as well as professionals to better understand basic statistical concepts. 100 Questions (and Answers) About Statistics addresses the essential questions that students ask about statistics in a concise and accessible way. It is perfect for instructors, students, and practitioners as a supplement to more comprehensive materials, or as a desk reference with quick answers to the most frequently asked questions.

The Science of Answering Questions: A Statistical Approach introduces students to the process of determining an answer to a question or problem through the collection of information, the use of statistical tools on the information, and reaching a conclusion based on the results. Opening chapters explore the evidence needed to answer the question of interest. Students learn about variables, levels of measurement, populations, samples, and sampling, as well as commonly used and freely available statistical software that can be used in statistical analyses. Additional chapters introduce ways to display and describe information collected from the sample, including summaries, summary tables, and graphs. Descriptive statistics and inferential statistics are covered. Readers explore descriptors, predictors, point estimation, deviation and variance, probability distributions, and interval estimation. Chapters in the latter half of the text focus on answering different questions of interest or the same question with different types of collected information. These chapters cover hypothesis testing, one sample proportion, multinomial, pre-post, homogeneity, correlation, independence, and more. Appendices provide students with helpful references related to critical values and standard normal probabilities. Providing students with a complete yet accessible introduction, The Science of Answering Questions is an excellent introductory resource for a course in statistics.

James Dean Brown ("JD"), currently Professor of Second Language Studies at the University of Hawaii at Manoa, has lectured and taught around the world and has published numerous articles and books on language testing, curriculum design, research methods, and connected speech. For close to twenty years, Professor Brown has contributed a regular column called Statistics Corner to Shiken, the biannual publication of the Testing and Evaluation Special Interest Group (TEVAL) of the Japan Association for Language Teaching (JALT). In his column, JD answers questions submitted by readers about language testing and statistics in an informal and easy to understand format. This volume brings together in one convenient location, forty-one Statistics Corner columns-updated, arranged thematically, and fully indexed. Presented in a question and answer format, the clear and concise explanations are both accessible to novices and engaging to experts. Topics addressed include: Second language testing strategies Likert items and scales of measurement Validity and reliability of tests and questionnaires Item analysis techniques for norm-referenced and criterion-referenced tests Conducting and interpreting principle component and factor analyses Planning and interpreting qualitative, quantitative, and mixed-methods research Clear explanations of the meaning and interpretation of frequently reported statistics such as Cronbach's alpha, standard error, confidence intervals, eta squared, Cohen's Kappa, skewness and kurtosis, and more."

A New York Times bestseller "Brilliant, funny…the best math teacher you never had." —San Francisco Chronicle Once considered tedious, the field of statistics is rapidly evolving into a discipline Hal Varian, chief economist at Google, has actually called "sexy." From batting averages and political polls to game shows and medical research, the real-world application of statistics continues to grow by leaps and bounds. How can we catch schools that cheat on standardized tests? How does Netflix know which movies you’ll like? What is causing the rising incidence of autism? As best-selling author Charles Wheelan shows us in Naked Statistics, the right data and a few well-chosen statistical tools can help us answer these questions and more. For those who slept through Stats 101, this book is a lifesaver. Wheelan strips away the arcane and technical details and focuses on the underlying intuition that drives statistical analysis. He clarifies key concepts such as inference, correlation, and regression analysis, reveals how biased or careless parties can manipulate or misrepresent data, and shows us how brilliant and creative researchers are exploiting the valuable data from natural experiments to tackle thorny questions. And in Wheelan’s trademark style, there’s not a dull page in sight. You’ll encounter clever Schlitz Beer marketers leveraging basic probability, an International Sausage Festival illuminating the tenets of the central limit theorem, and a head-scratching choice from the famous game show Let’s Make a Deal—and you’ll come away with insights each time. With the wit, accessibility, and sheer fun that turned Naked Economics into a bestseller, Wheelan defies the odds yet again by bringing another essential, formerly unglamorous discipline to life.

"Learning Statistics with R" covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software and adopting a light, conversational style throughout. The book discusses how to get started in R, and gives an introduction to data manipulation and writing scripts. From a statistical perspective, the book discusses descriptive statistics and graphing first, followed by chapters on probability theory, sampling and estimation, and null hypothesis testing. After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book. For more information (and the opportunity to check the book out before you buy!) visit http://ua.edu.au/ccs/teaching/lsr or http://learningstatisticswithr.com

This book illustrates step-by-step how to use SPSS 7.5 for Windows to answer both simple and complex research questions. It describes in non-technical language how to interpret a wide range of SPSS outputs. It enables the user to develop skills on how to choose the appropriate statistics, interpret the outputs, and write about the outputs and the meaning of the results.