Normal and Sampling Distribution (A'level H2 Math) PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Normal and Sampling Distribution (A'level H2 Math) PDF full book. Access full book title Normal and Sampling Distribution (A'level H2 Math) by Lee Jun Cai. Download full books in PDF and EPUB format.
Author: Lee Jun Cai
Publisher: AcesMath!
ISBN:
Category : Education
Languages : en
Pages : 41
Get Book Here
Book Description
Confused about the various graph transformation taught in school? This book on Normal and Sampling Distribution seeks to offer a condensed version of what you need to know for A-Levels H2 Mathematics, alongside with detailed worked examples and extra practice questions. Tips on certain question types are provided to aid in smoothing the working process when dealing with them.
Author: Lee Jun Cai
Publisher: AcesMath!
ISBN:
Category : Education
Languages : en
Pages : 41
Get Book Here
Book Description
Confused about the various graph transformation taught in school? This book on Normal and Sampling Distribution seeks to offer a condensed version of what you need to know for A-Levels H2 Mathematics, alongside with detailed worked examples and extra practice questions. Tips on certain question types are provided to aid in smoothing the working process when dealing with them.
Author: Larry Wasserman
Publisher: Springer Science & Business Media
ISBN: 0387217363
Category : Mathematics
Languages : en
Pages : 446
Get Book Here
Book Description
Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like non-parametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analysing data.
Author: Lee Jun Cai
Publisher: AcesMath!
ISBN:
Category : Mathematics
Languages : en
Pages : 38
Get Book Here
Book Description
Confused about the various graph transformation taught in school? This book on Applications of Sampling - Hypothesis Testing and Correlation & Regression seeks to offer a condensed version of what you need to know for A-Levels H2 Mathematics, alongside with detailed worked examples and extra practice questions. Tips on certain question types are provided to aid in smoothing the working process when dealing with them.
Author: Michael J. Evans
Publisher: Macmillan
ISBN: 9780716747420
Category : Mathematics
Languages : en
Pages : 704
Get Book Here
Book Description
Unlike traditional introductory math/stat textbooks, Probability and Statistics: The Science of Uncertainty brings a modern flavor based on incorporating the computer to the course and an integrated approach to inference. From the start the book integrates simulations into its theoretical coverage, and emphasizes the use of computer-powered computation throughout.* Math and science majors with just one year of calculus can use this text and experience a refreshing blend of applications and theory that goes beyond merely mastering the technicalities. They'll get a thorough grounding in probability theory, and go beyond that to the theory of statistical inference and its applications. An integrated approach to inference is presented that includes the frequency approach as well as Bayesian methodology. Bayesian inference is developed as a logical extension of likelihood methods. A separate chapter is devoted to the important topic of model checking and this is applied in the context of the standard applied statistical techniques. Examples of data analyses using real-world data are presented throughout the text. A final chapter introduces a number of the most important stochastic process models using elementary methods. *Note: An appendix in the book contains Minitab code for more involved computations. The code can be used by students as templates for their own calculations. If a software package like Minitab is used with the course then no programming is required by the students.
Author: Andrew N O'Connor
Publisher: RIAC
ISBN: 1933904062
Category : Mathematics
Languages : en
Pages : 220
Get Book Here
Book Description
The book provides details on 22 probability distributions. Each distribution section provides a graphical visualization and formulas for distribution parameters, along with distribution formulas. Common statistics such as moments and percentile formulas are followed by likelihood functions and in many cases the derivation of maximum likelihood estimates. Bayesian non-informative and conjugate priors are provided followed by a discussion on the distribution characteristics and applications in reliability engineering.
Author: Deborah J. Rumsey
Publisher: John Wiley & Sons
ISBN: 1119293529
Category : Mathematics
Languages : en
Pages : 423
Get Book Here
Book Description
The 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: Victor M. Panaretos
Publisher: Birkhäuser
ISBN: 3319283413
Category : Mathematics
Languages : en
Pages : 190
Get Book Here
Book Description
This textbook provides a coherent introduction to the main concepts and methods of one-parameter statistical inference. Intended for students of Mathematics taking their first course in Statistics, the focus is on Statistics for Mathematicians rather than on Mathematical Statistics. The goal is not to focus on the mathematical/theoretical aspects of the subject, but rather to provide an introduction to the subject tailored to the mindset and tastes of Mathematics students, who are sometimes turned off by the informal nature of Statistics courses. This book can be used as the basis for an elementary semester-long first course on Statistics with a firm sense of direction that does not sacrifice rigor. The deeper goal of the text is to attract the attention of promising Mathematics students.
Author: G. Jay Kerns
Publisher: Lulu.com
ISBN: 0557249791
Category : Education
Languages : en
Pages : 388
Get Book Here
Book Description
This is a textbook for an undergraduate course in probability and statistics. The approximate prerequisites are two or three semesters of calculus and some linear algebra. Students attending the class include mathematics, engineering, and computer science majors.
Author: Deborah J. Rumsey
Publisher: John Wiley & Sons
ISBN: 0470466464
Category : Mathematics
Languages : en
Pages : 411
Get Book Here
Book Description
The ideal supplement and study guide for students preparing for advanced statistics Packed with fresh and practical examples appropriate for a range of degree-seeking students, Statistics II For Dummies helps any reader succeed in an upper-level statistics course. It picks up with data analysis where Statistics For Dummies left off, featuring new and updated examples, real-world applications, and test-taking strategies for success. This easy-to-understand guide covers such key topics as sorting and testing models, using regression to make predictions, performing variance analysis (ANOVA), drawing test conclusions with chi-squares, and making comparisons with the Rank Sum Test.
Author: Andrew Gelman
Publisher: CRC Press
ISBN: 1439840954
Category : Mathematics
Languages : en
Pages : 677
Get Book Here
Book Description
Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied approach to analysis using up-to-date Bayesian methods. The authors—all leaders in the statistics community—introduce basic concepts from a data-analytic perspective before presenting advanced methods. Throughout the text, numerous worked examples drawn from real applications and research emphasize the use of Bayesian inference in practice. New to the Third Edition Four new chapters on nonparametric modeling Coverage of weakly informative priors and boundary-avoiding priors Updated discussion of cross-validation and predictive information criteria Improved convergence monitoring and effective sample size calculations for iterative simulation Presentations of Hamiltonian Monte Carlo, variational Bayes, and expectation propagation New and revised software code The book can be used in three different ways. For undergraduate students, it introduces Bayesian inference starting from first principles. For graduate students, the text presents effective current approaches to Bayesian modeling and computation in statistics and related fields. For researchers, it provides an assortment of Bayesian methods in applied statistics. Additional materials, including data sets used in the examples, solutions to selected exercises, and software instructions, are available on the book’s web page.
