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Author: M. D. Edge
Publisher:
Published: 2019
Total Pages: 318
ISBN-13: 0198827628
DOWNLOAD EBOOKFocuses on detailed instruction in a single statistical technique, simple linear regression (SLR), with the goal of gaining tools, understanding, and intuition that can be applied to other contexts.
Author: Daniel Navarro
Publisher: Lulu.com
Published: 2013-01-13
Total Pages: 617
ISBN-13: 1326189727
DOWNLOAD EBOOK"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
Author: David M Lane
Publisher:
Published: 2014-12-02
Total Pages: 406
ISBN-13: 9781687894250
DOWNLOAD EBOOKOnline Statistics: An Interactive Multimedia Course of Study is a resource for learning and teaching introductory statistics. It contains material presented in textbook format and as video presentations. This resource features interactive demonstrations and simulations, case studies, and an analysis lab.This print edition of the public domain textbook gives the student an opportunity to own a physical copy to help enhance their educational experience. This part I features the book Front Matter, Chapters 1-10, and the full Glossary. Chapters Include:: I. Introduction, II. Graphing Distributions, III. Summarizing Distributions, IV. Describing Bivariate Data, V. Probability, VI. Research Design, VII. Normal Distributions, VIII. Advanced Graphs, IX. Sampling Distributions, and X. Estimation. Online Statistics Education: A Multimedia Course of Study (http: //onlinestatbook.com/). Project Leader: David M. Lane, Rice University.
Author: Therese M. Donovan
Publisher: Oxford University Press, USA
Published: 2019
Total Pages: 430
ISBN-13: 0198841299
DOWNLOAD EBOOKThis is an entry-level book on Bayesian statistics written in a casual, and conversational tone. The authors walk a reader through many sample problems step-by-step to provide those with little background in math or statistics with the vocabulary, notation, and understanding of the calculations used in many Bayesian problems.
Author: Isadore Newman
Publisher: University Press of America
Published: 1994
Total Pages: 302
ISBN-13: 9780819194206
DOWNLOAD EBOOKThis new edition emphasizes and facilitates the conceptual understanding of statistics and statistical concepts for the purpose of reading and accurately interpreting research literature. The use of hand calculators is deemphasized. Instead, computer example setups are supplied for SPSS and SAS.
Author: Chirag Shah
Publisher: Cambridge University Press
Published: 2020-04-02
Total Pages: 459
ISBN-13: 1108472443
DOWNLOAD EBOOKAn introductory textbook offering a low barrier entry to data science; the hands-on approach will appeal to students from a range of disciplines.
Author: Barbara Illowsky
Publisher:
Published: 2023-12-13
Total Pages: 2106
ISBN-13:
DOWNLOAD EBOOKIntroductory Statistics 2e provides an engaging, practical, and thorough overview of the core concepts and skills taught in most one-semester statistics courses. The text focuses on diverse applications from a variety of fields and societal contexts, including business, healthcare, sciences, sociology, political science, computing, and several others. The material supports students with conceptual narratives, detailed step-by-step examples, and a wealth of illustrations, as well as collaborative exercises, technology integration problems, and statistics labs. The text assumes some knowledge of intermediate algebra, and includes thousands of problems and exercises that offer instructors and students ample opportunity to explore and reinforce useful statistical skills. This is an adaptation of Introductory Statistics 2e by OpenStax. You can access the textbook as pdf for free at openstax.org. Minor editorial changes were made to ensure a better ebook reading experience. Textbook content produced by OpenStax is licensed under a Creative Commons Attribution 4.0 International License.
Author: Deborah J. Rumsey
Publisher: John Wiley & Sons
Published: 2016-06-07
Total Pages: 423
ISBN-13: 1119293529
DOWNLOAD EBOOKThe fun and easy way to get down to business with statistics Stymied by statistics? No fear? this friendly guide offers clear, practical explanations of statistical ideas, techniques, formulas, and calculations, with lots of examples that show you how these concepts apply to your everyday life. Statistics For Dummies shows you how to interpret and critique graphs and charts, determine the odds with probability, guesstimate with confidence using confidence intervals, set up and carry out a hypothesis test, compute statistical formulas, and more. Tracks to a typical first semester statistics course Updated examples resonate with today's students Explanations mirror teaching methods and classroom protocol Packed with practical advice and real-world problems, Statistics For Dummies gives you everything you need to analyze and interpret data for improved classroom or on-the-job performance.
Author: Ai Publishing
Publisher:
Published: 2020-04-18
Total Pages: 188
ISBN-13: 9781734790115
DOWNLOAD EBOOKStatistics for Beginners in Data Science Statistical methods are an integral part of data science. Hence, a formal training in statistics is indispensable for data scientists. If you are keen on getting your foot into the lucrative data science and analysis universe, you need to have a fundamental understanding of statistical analysis. Besides, Python is a versatile programming language you need to master to become a career data scientist. As a data scientist, you will identify, clean, explore, analyze, and interpret trends or possible patterns in complex data sets. The explosive growth of Big Data means you have to manage enormous amounts of data, clean it, manipulate it, and process it. Only then the most relevant data can be used. Python is a natural data science tool as it has an assortment of useful libraries, such as Pandas, NumPy, SciPy, Matplotlib, Seaborn, StatsModels, IPython, and several more. And Python's focus on simplicity makes it relatively easy for you to learn. Importantly, the ease of performing repetitive tasks saves you precious time. Long story short--Python is simply a high-priority data science tool. How Is This Book Different? The book focuses equally on the theoretical as well as practical aspects of data science. You will learn how to implement elementary data science tools and algorithms from scratch. The book contains an in-depth theoretical and analytical explanation of all data science concepts and also includes dozens of hands-on, real-life projects that will help you understand the concepts better. The ready-to-access Python codes at various places right through the book are aimed at shortening your learning curve. The main goal is to present you with the concepts, the insights, the inspiration, and the right tools needed to dive into coding and analyzing data in Python. The main benefit of purchasing this book is you get quick access to all the extra content provided with this book--Python codes, exercises, references, and PDFs--on the publisher's website, at no extra price. You get to experiment with the practical aspects of Data Science right from page 1. Beginners in Python and statistics will find this book extremely informative, practical, and helpful. Even if you aren't new to Python and data science, you'll find the hands-on projects in this book immensely helpful. The topics covered include: Introduction to Statistics Getting Familiar with Python Data Exploration and Data Analysis Pandas, Matplotlib, and Seaborn for Statistical Visualization Exploring Two or More Variables and Categorical Data Statistical Tests and ANOVA Confidence Interval Regression Analysis Classification Analysis Click the BUY button and download the book now to start learning and coding Python for Data Science.
Author: Roger Watt
Publisher: SAGE
Published: 2019-03-30
Total Pages: 404
ISBN-13: 1526481618
DOWNLOAD EBOOKThis concise, easy-to-understand and highly visual book helps students to understand the principles behind the many statistical practices. This text helps students to build a mental map to enable them to work their way through tests and procedures with a better level of understanding (and ultimately feel more confident and get better grades). Statistical analysis will also be covered in the book in the same simple-to-follow way, without messy details or complicated formulae. However, this approach does not lead to simple understanding. Instead it allows students to really grasp how to use, and be creative with, statistics. Key features: A principles-based approach, helping students to apply and adapt their skills to a variety of situation Test out principles in practice on the companion website with statistics scenarios Carefully designed graphics to explain statistical principles Links to relevant sources / further reading for statistical packages, so the book can be used as a portal to/ springboard for further study. Developed in conjunction with students means this book answers the key challenges students face. Based on a BPS commended programme Supported by a wealth of online resources at www.sagepub.co.uk/statisticsforpsychology
