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The fast and easy way to ace your statics course Does the study of statics stress you out? Does just the thought of mechanics make you rigid? Thanks to this book, you can find balance in the study of this often-intimidating subject and ace even the most challenging university-level courses. Statics For Dummies gives you easy-to-follow, plain-English explanations for everything you need to grasp the study of statics. You'll get a thorough introduction to this foundational branch of engineering and easy-to-follow coverage of solving problems involving forces on bodies at rest; vector algebra; force systems; equivalent force systems; distributed forces; internal forces; principles of equilibrium; applications to trusses, frames, and beams; and friction. Offers a comprehensible introduction to statics Covers all the major topics you'll encounter in university-level courses Plain-English guidance help you grasp even the most confusing concepts If you're currently enrolled in a statics course and looking for a friendlier way to get a handle on the subject, Statics For Dummies has you covered.
Researchers across the natural and social sciences find themselves navigating tremendous amounts of new data. Making sense of this flood of information requires more than the rote application of formulaic statistical methods. The premise of Statistical Thinking from Scratch is that students who want to become confident data analysts are better served by a deep introduction to a single statistical method than by a cursory overview of many methods. In particular, this book focuses on simple linear regression-a method with close connections to the most important tools in applied statistics-using it as a detailed case study for teaching resampling-based, likelihood-based, and Bayesian approaches to statistical inference. Considering simple linear regression in depth imparts an idea of how statistical procedures are designed, a flavour for the philosophical positions one assumes when applying statistics, and tools to probe the strengths of one's statistical approach. Key to the book's novel approach is its mathematical level, which is gentler than most texts for statisticians but more rigorous than most introductory texts for non-statisticians. Statistical Thinking from Scratch is suitable for senior undergraduate and beginning graduate students, professional researchers, and practitioners seeking to improve their understanding of statistical methods across the natural and social sciences, medicine, psychology, public health, business, and other fields.
Online 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.
This 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.
An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wrote An Introduction to Statistical Learning, With Applications in R (ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users.
Basic Statistics with R: Reaching Decisions with Data provides an understanding of the processes at work in using data for results. Sections cover data collection and discuss exploratory analyses, including visual graphs, numerical summaries, and relationships between variables - basic probability, and statistical inference - including hypothesis testing and confidence intervals. All topics are taught using real-data drawn from various fields, including economics, biology, political science and sports. Using this wide variety of motivating examples allows students to directly connect and make statistics essential to their field of interest, rather than seeing it as a separate and ancillary knowledge area. In addition to introducing students to statistical topics using real data, the book provides a gentle introduction to coding, having the students use the statistical language and software R. Students learn to load data, calculate summary statistics, create graphs and do statistical inference using R with either Windows or Macintosh machines. Features real-data to give students an engaging practice to connect with their areas of interest Evolves from basic problems that can be worked by hand to the elementary use of opensource R software Offers a direct, clear approach highlighted by useful visuals and examples
Introductory Statistics follows scope and sequence requirements of a one-semester introduction to statistics course and is geared toward students majoring in fields other than math or engineering. The text assumes some knowledge of intermediate algebra and focuses on statistics application over theory. Introductory Statistics includes innovative practical applications that make the text relevant and accessible, as well as collaborative exercises, technology integration problems, and statistics labs. Senior Contributing Authors Barbara Illowsky, De Anza College Susan Dean, De Anza College Contributing Authors Daniel Birmajer, Nazareth College Bryan Blount, Kentucky Wesleyan College Sheri Boyd, Rollins College Matthew Einsohn, Prescott College James Helmreich, Marist College Lynette Kenyon, Collin County Community College Sheldon Lee, Viterbo University Jeff Taub, Maine Maritime Academy
This historic book may have numerous typos and missing text. Purchasers can usually download a free scanned copy of the original book (without typos) from the publisher. Not indexed. Not illustrated. 1889 edition. Excerpt: ...it is obvious that W-2P. There are three systems of pulleys usually described in text-books. The First System of Pulleys. 125. In the first system, which is sometimes described as that in which each pulley hangs by a separate string, the weight is attached to the lowest pulley: this is supported by a rope one end of which is attached to a fixed beam and the other end to the pulley next above, which is again supFig. 64. ported in a similar way. The power is applied at the end of the rope supporting the highest pulley. The straight portions of the ropes are all vertical. Condition of equilibrium. (1) When the pulleys are supposed weightless. Let there be n pulleys, and let the tensions of the ropes supporting them beginning with the lowest be Tlt T3...Tn. From the equilibrium of the first (lowest) pulley 27;= W. From the equilibrium of the others, we have 2T = T 2T3=Tv...2T = Ta, 2r =r, _1, .'. W= 27; = 2'. Ts = 2'.Ta = 2. T = 2." Tn = 2." P. (2) When the pulleys are heavy. Let w, wa, w3...wn be the weights of the pulleys beginning with the lowest. We have seen from (1) that a weight W attached to the W lowest pulley causes a force to be transmitted to the rope round the highest (the nth). Similarly the weight wl will cause a force--I to be transmitted to the same rope, and the weight w2 a force r, the weight w3 a force, and so on. Hence P the tension of the rope round the highest pulley is the sum of the forces due to these separate causes, . _ W w, wa w, w--P-n +-r+ +--T-+-----2 2 2" 2 2.-, 2." P= W+ Wl + 2W2 + 2nZV3 +...2'lWlt. Cor. It is clear from the above that the weights of the pulleys act against the Power as the Power is greater when the pulleys have weight. EXAMPLES XXXI. I. If there are four...