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  • Empirical Research in Statistics Education
    Empirical Research in Statistics Education

    This ICME-13 Topical Survey provides a review of recent research into statistics education, with a focus on empirical research published in established educational journals and on the proceedings of important conferences on statistics education.It identifies and addresses six key research topics, namely: teachers’ knowledge; teachers’ role in statistics education; teacher preparation; students’ knowledge; students’ role in statistics education; and how students learn statistics with the help of technology.For each topic, the survey builds upon existing reviews, complementing them with the latest research.

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  • Doing Quantitative Research in Education with IBM SPSS Statistics
    Doing Quantitative Research in Education with IBM SPSS Statistics

    This essential guide for education students and researchers explains how to use quantitative methods for analysing educational data using IBM SPSS Statistics. By using datasets from real-life educational research, it demonstrates key statistical techniques that you will need to know, explaining how each procedure can by run on IBM SPSS Statistics.Datasets discussed in the book are downloadable, allowing you to hone your skills as you read. In this third edition, explanations have been updated with figures and screenshots from SPSS version 28, alongside a range of new research examples and updated further reading. Daniel Muijs is Dean of the Faculty of Education and Society at Academica University of Applied Sciences in Amsterdam.

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  • Practical Statistics for Medical Research
    Practical Statistics for Medical Research

    Most medical researchers, whether clinical or non-clinical, receive some background in statistics as undergraduates.However, it is most often brief, a long time ago, and largely forgotten by the time it is needed.Furthermore, many introductory texts fall short of adequately explaining the underlying concepts of statistics, and often are divorced from the reality of conducting and assessing medical research.Practical Statistics for Medical Research is a problem-based text for medical researchers, medical students, and others in the medical arena who need to use statistics but have no specialized mathematics background.Explores topics of particular importance in clinical practice, including diagnostic tests, method comparison, and observer agreementUtilizes real data throughout and includes dozens of interesting data setsDiscusses the use and misuse of statistics, enabling readers to judge the appropriateness of methods and interpretations published in medical journalsDescribes the main statistical methods for comparing data collected from different groups of individuals or for relating different observations from the same peopleProvides many problems, all with detailed solutionsThe author draws on twenty years of experience as a consulting medical statistician to provide clear explanations to key statistical concepts, with a firm emphasis on practical aspects of designing and analyzing medical research.The text gives special attention to the presentation and interpretation of results and the many real problems that arise in medical research.

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  • Research Methods, Statistics, and Applications
    Research Methods, Statistics, and Applications

    Research Methods, Statistics, and Applications by Kathrynn A.Adams and Eva K. McGuire is designed to give students the experience of being a researcher by combining the interrelated concepts of research methods and statistics to better explain how the research process incorporates both elements.Employing a conversational tone throughout, coupled with an emphasis on decision-making, this best-selling text will spark students’ interest in conducting research and improve their ability to critically analyze research in their daily lives. The Third Edition includes a new chapter on measurement to better highlight its critical importance, updates for the 7th edition of the Publication Manual of the American Psychological Association, new examples related to social justice, additional sections on qualitative research methods, and more thorough integration of research ethics information and tips throughout each chapter.

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  • Which topics are suitable for a statistics research paper?

    Topics suitable for a statistics research paper include: 1. Analysis of large datasets using statistical methods 2. Application of statistical techniques in various fields such as healthcare, economics, social sciences, and environmental studies 3. Comparison of different statistical models and their effectiveness in solving real-world problems 4. Development of new statistical methods or algorithms 5. Evaluation of the impact of specific interventions or policies using statistical analysis. These topics provide opportunities to explore the practical application of statistical methods and contribute to the advancement of statistical knowledge in various domains.

  • Is this question about inferential statistics or descriptive statistics?

    This question is about distinguishing between inferential statistics and descriptive statistics. Inferential statistics involves making predictions or inferences about a population based on a sample of data, while descriptive statistics involves summarizing and describing the characteristics of a dataset.

  • How difficult is statistics?

    Statistics can be challenging for some people due to its complex concepts and mathematical calculations. Understanding statistical theories and applying them to real-world data sets can be difficult for those who are not familiar with the subject. However, with practice and dedication, many people can grasp the fundamentals of statistics and become proficient in analyzing data. It is important to seek help from teachers, tutors, or online resources if you are struggling with statistics to improve your understanding and skills.

  • What are NBA statistics?

    NBA statistics are numerical data that track the performance of players and teams in the National Basketball Association. These statistics include a wide range of metrics such as points scored, rebounds, assists, steals, blocks, shooting percentages, turnovers, and many others. They are used to evaluate and compare the performance of players and teams, as well as to analyze trends and make strategic decisions. NBA statistics are an essential tool for coaches, analysts, and fans to understand the game and its players better.

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  • Research Methods and Statistics in Psychology
    Research Methods and Statistics in Psychology

    Updated with new chapters on multiple regression and high-level research methods, this 4th edition of Research Methods and Statistics in Psychology delivers all you need to develop a practical understanding of both quantitative and qualitative approaches to research in psychology.In particular, this book guides you through the range of choices and considerations involved in research design, data analysis and report presentation. Your learning is supported by a range of features, both in the book and online.These include: Research Bites, to provide you with practical insights that arise from the most current research practice Test yourself questions, to check your understanding Exercises, to test your knowledge Glossary, to help you with key terms Research evaluation and improvement checklists – quick summaries of best practice for you to refer to Online appendices, including data sets to practice with! And much more… S. Alexander Haslam is Professor of Psychology and Laureate Fellow at the University of Queensland Craig McGarty is an adjunct professor at Western Sydney University Tegan Cruwys is Associate Professor and NHMRC Emerging Leadership Fellow at the Australian National University Niklas K.Steffens is Associate Professor and Director of the Centre for Business and Organisational Psychology at the University of Queensland

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  • Research Methods and Statistics in Psychology
    Research Methods and Statistics in Psychology

    Updated with new chapters on multiple regression and high-level research methods, this 4th edition of Research Methods and Statistics in Psychology delivers all you need to develop a practical understanding of both quantitative and qualitative approaches to research in psychology.In particular, this book guides you through the range of choices and considerations involved in research design, data analysis and report presentation. Your learning is supported by a range of features, both in the book and online.These include: Research Bites, to provide you with practical insights that arise from the most current research practice Test yourself questions, to check your understanding Exercises, to test your knowledge Glossary, to help you with key terms Research evaluation and improvement checklists – quick summaries of best practice for you to refer to Online appendices, including data sets to practice with! And much more… S. Alexander Haslam is Professor of Psychology and Laureate Fellow at the University of Queensland Craig McGarty is an adjunct professor at Western Sydney University Tegan Cruwys is Associate Professor and NHMRC Emerging Leadership Fellow at the Australian National University Niklas K.Steffens is Associate Professor and Director of the Centre for Business and Organisational Psychology at the University of Queensland

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  • Statistics for Marketing and Consumer Research
    Statistics for Marketing and Consumer Research

    Balancing simplicity with technical rigour, this practical guide to the statistical techniques essential to research in marketing and related fields, describes each method as well as showing how they are applied. The book is accompanied by two real data sets to replicate examples and with exercises to solve, as well as detailed guidance on the use of appropriate software including: - 750 powerpoint slides with lecture notes and step-by-step guides to run analyses in SPSS (also includes screenshots) - 136 multiple choice questions for tests This is augmented by in-depth discussion of topics including: - Sampling - Data management and statistical packages - Hypothesis testing - Cluster analysis - Structural equation modelling

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  • Modern Bayesian Statistics in Clinical Research
    Modern Bayesian Statistics in Clinical Research

    The current textbook has been written as a help to medical / health professionals and students for the study of modern Bayesian statistics, where posterior and prior odds have been replaced with posterior and prior likelihood distributions.Why may likelihood distributions better than normal distributions estimate uncertainties of statistical test results?Nobody knows for sure, and the use of likelihood distributions instead of normal distributions for the purpose has only just begun, but already everybody is trying and using them.SPSS statistical software version 25 (2017) has started to provide a combined module entitled Bayesian Statistics including almost all of the modern Bayesian tests (Bayesian t-tests, analysis of variance (anova), linear regression, crosstabs etc.).Modern Bayesian statistics is based on biological likelihoods, and may better fit clinical data than traditional tests based normal distributions do.This is the first edition to systematically implymodern Bayesian statistics in traditional clinical data analysis.This edition also demonstrates that Markov Chain Monte Carlo procedures laid out as Bayesian tests provide more robust correlation coefficients than traditional tests do.It also shows that traditional path statistics are both textually and conceptionally like Bayes theorems, and that structural equations models computed from them are the basis of multistep regressions, as used with causal Bayesian networks.

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  • What are English statistics?

    English statistics refer to data and information related to the English language, including its usage, speakers, and variations. This can include data on the number of English speakers worldwide, the prevalence of English as a second language, and trends in language learning. English statistics can also encompass information on dialects, accents, and regional variations of the language. Overall, English statistics provide valuable insights into the global impact and diversity of the English language.

  • What is descriptive statistics?

    Descriptive statistics is a branch of statistics that focuses on summarizing and describing the main features of a dataset. It involves organizing, summarizing, and presenting data in a meaningful way, such as through measures of central tendency (mean, median, mode) and measures of variability (range, standard deviation). Descriptive statistics help to simplify and interpret large amounts of data, making it easier to understand and draw conclusions from the information presented. It is an essential tool in data analysis for researchers, scientists, and decision-makers in various fields.

  • Which statistics are better?

    The statistics that are better are the ones that are accurate, reliable, and relevant to the topic being discussed. It is important to consider the source of the statistics, the methodology used to collect the data, and whether the statistics are up-to-date. Additionally, statistics that are presented in a clear and understandable manner are also considered better as they can effectively communicate the information to the audience.

  • What are the research designs in statistics and how do you plan experiments?

    In statistics, there are several research designs, including experimental, observational, and quasi-experimental designs. Experimental designs involve manipulating one or more variables to observe the effect on another variable, while observational designs involve simply observing and recording data without any manipulation. Quasi-experimental designs are similar to experimental designs but lack random assignment of participants to groups. When planning experiments, it is important to clearly define the research question, identify the variables to be studied, and determine the appropriate research design. It is also important to consider factors such as sample size, randomization, and control groups to ensure the validity and reliability of the results. Additionally, ethical considerations and potential biases should be taken into account when planning experiments.

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