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4434Statistics Using Technology
http://www.merlot.org/merlot/viewMaterial.htm?id=908731
This is a statistics textbook to be used in an introductory statistics class. This book uses technology to calculate probabilities. The approach to this textbook is to ask people to interpret statistics and think statistically. Chapter 1: Statistical Basics Section 1.1: What is Statistics? Section 1.2: Sampling Methods Section 1.3: Experimental Design Section 1.4: How Not to Do Statistics Chapter 2: Graphical Descriptions of Data Section 2.1: Qualitative Data Section 2.2: Quantitative Data Section 2.3: Other Graphical Representations of Data Chapter 3: Numerical Descriptions of Data Section 3.1: Measures of Center Section 3.2: Measures of Spread Section 3.3: Ranking Chapter 4: Probability Section 4.1: Empirical Probability Section 4.2: Theoretical Probability Section 4.3: Conditional Probability Section 4.4: Counting Techniques Chapter 5: Discrete Probability Distributions Section 5.1: Basics of Probability Distributions Section 5.2: Binomial Probability Distribution Section 5.3: Mean and Standard Deviation of Binomial Distribution Chapter 6: Continuous Probability Distributions Section 6.1: Uniform Distribution Section 6.2: Graphs of the Normal Distribution Section 6.3: Finding Probabilities for the Normal Distribution Section 6.4: Assessing Normality Section 6.5: Sampling Distribution and the Central Limit Theorem Chapter 7: One-Sample Inference Section 7.1: Basics of Hypothesis Testing Section 7.2: One-Sample Proportion Test Section 7.3: One-Sample Test for the Mean Chapter 8: Estimation Section 8.1: Basics of Confidence Intervals Section 8.2: One-Sample Interval for the Proportion Section 8.3: One-Sample Interval for the Mean Chapter 9: Two-Sample Inference Section 9.1: Paired Samples for Two Means Section 9.2: Independent Samples for Two Means Section 9.3: Two Proportions Chapter 10: Regression and Correlation Section 10.1: Regression Section 10.2: Correlation Section 10.3: Inference for Regression and Correlation Chapter 11: Chi-Square and ANOVA Tests Section 11.1: Chi-Square Test for Independence Section 11.2: Chi-Square Goodness of Fit Section 11.3: Analysis of Variance (ANOVA)Probability and Statistics
http://www.merlot.org/merlot/viewMaterial.htm?id=906143
'This module consists of three units:Unit 1: Descriptive Statistics and Probability DistributionsDescriptive statistics in unit one is developed either as an extension of secondary mathematics or as an introduction to first time learners of statistics. It introduces the measures of dispersion in statistics. The unit also introduces the concept of probability and the theoretical treatment of probability.Unit 2: Random variables and Test DistributionsThis unit requires Unit 1 as a prerequisite. It develops from the moment and moment generating functions, Markov and Chebychev inequalities, special univariate distributions, bivariate probability distributions and analyses conditional probabilities. The unit gives insights into the analysis of correlation coefficients and distribution functions of random variables such as the Chi-square, t and F.Unit 3: Probability TheoryThis unit builds up from unit 2. It analyses probability using indicator functions. It introduces Bonferoni inequality random vectors,, generating functions, characteristic functions and statistical independence random samples. It develops further the concepts of functions of several random variables and independence of X and S2 in normal samples order statistics. The unit summarises with the treatment of convergence and limit theorems.'Collaborative Statistics
http://www.merlot.org/merlot/viewMaterial.htm?id=906156
'Our emphasis in this text is on four main concepts:thinking statisticallyincorporating technologyworking collaborativelywriting thoughtfullyThese concepts are integral to our course. Students learn the best by actively participating, not by just watching and listening. Teaching should be highly interactive. Students need to be thoroughly engaged in the learning process in order to make sense of statistical concepts. Collaborative Statistics provides techniques for students to write across the curriculum, to collaborate with their peers, to think statistically, and to incorporate technology.This book takes students step by step. The text is interactive. Therefore, students can immediately apply what they read. Once students have completed the process of problem solving, they can tackle interesting and challenging problems relevant to today’s world. The problems require the students to apply their newly found skills. In addition, technology (TI-83 graphing calculators are highlighted) is incorporated throughout the text and the problems, as well as in the special group activities and projects. The book also contains labs that use real data and practices that lead students step by step through the problem solving process.At De Anza, along with hundreds of other colleges across the country, the college audience involves a large number of ESL students as well as students from many disciplines. The ESL students, as well as the non-ESL students, have been especially appreciative of this text. They find it extremely readable and understandable. Collaborative Statistics has been used in classes that range from 20 to 120 students, and in regular, honor, and distance learning classes.'Introduction to Probability
http://www.merlot.org/merlot/viewMaterial.htm?id=905939
'Our book emphasizes the use of computing to simulate experiments and make computations. We have prepared a set of programs to go with the book. We have Mathematica, Maple, and TrueBASIC versions of these programs. You can download the programs from this location. We also have experimental versions of the programs as Java applets written for us by Julian Devlin. The answers to the odd-numbered problems are available from this website. We would be happy to provide the solutions to all of the exercises to instructors of courses that use this book'Table of ContentsDiscrete Probability DistributionsContinuous Probability DistributionsCombinatoricsConditional ProbabilityDistributions and DensitiesExpected Value and VarianceSums of Random VariablesLaw of Large NumbersCentral Limit TheoremGenerating FunctionsMarkov ChainsRandom WalksOnline Statistics Education
http://www.merlot.org/merlot/viewMaterial.htm?id=905948
'This is a collaborative effort led by David Lane of Rice University. The core material is an interactive textbook that is best used over the Internet to take advantage of the embedded questions created in JavaScript. The PDF version that can be downloaded simply shows the answers in a different font following the questions.An attractive feature of Online Statistics is the suite of case studies making use of the actual data from published studies in the scientific literature and popular media. The data sets for the case studies are provided as Excel files. The website also provides some computational tools running in the browser for the statistical calculations needed for the analysis of the case studies, although instructors may prefer to use free software such as R or software already available at their institutions.Also part of the course is a set of 31 simulations illustrating key concepts such as the meaning of a 95% confidence interval. Some are written in JavaScript and run without difficulty, but others are written in Java and may present a problem because of the security concerns surrounding Java applets running in browsers.'Notes on regression & forecasting
http://www.merlot.org/merlot/viewMaterial.htm?id=905334
This web site contains notes and materials for a course on statistical forecasting that has been taught at the Fuqua School of Business, Duke University, for over 30 years. It covers basic techniques of data analysis as well as linear regression and time series forecasting. It emphasizes practical, hands-on computer modeling and is intended to serve as a complement rather than a substitute for traditional courses and reference materials on statistics. The material on regression is illustrated with output from RegressIt, a recently-developed free Excel add-in whose procedures for descriptive data analysis and ordinary linear regression offer high-quality output and support for good modeling practices. (http://regressit.com) This content on this site should be useful as self-instruction and reference material for students and practitioners who use regression and time series forecasting methods, as well as anyone who uses Excel-based tools for statistical analysis.D3mobile Metrology World League
http://www.merlot.org/merlot/viewMaterial.htm?id=899469
The University of Santiago de Compostela is organizing the D3MOBILE METROLOGY WORLD LEAGUE (www.d3mobile.es), an International Championship in 3D Precision Modeling on mobile phones aimed at strengthening the scientific vocation of 15-18 year old students around the world. The main objective of D3MOBILE is to disseminate importance of metrology, offering participants to develop 3D accuracy virtual models with a mobile phone. The championship winner will be the team that gets better results in measurements of an object.The main objectives of the Championship will be the simulation and stimulation of students’ research capacity in order to encourage their reflecting upon its importance when it comes to solving our environment’s problems and on the importance of decision making based on the analysis of the results obtained in an experimental process. Furthermore, the exercises proposed in this Championship encourage the educational use of the Internet and learning various technical computer programs which students might find useful for their future work.The aim of d3mobile.es is for students born between 1996 and 1998 all over the world to participate in a team championship that will reinforce their research capacity. They will be using equipment well known to all: mobile phones and computers. They will learn the basics of the photogrammetric technique with the help of one of their teachers and the free software they will be provided with. This methodology will allow them to build scaled tridimensional models of simple objects and it will only take them two afternoons of study to master it. Three mandatory exercises using specific free Internet programs will be carried out over the course of the Championship. The first exercise is oriented to training students whereas the remaining two will be subject to a grading process in order to grant the final award.Online Introductory Statistics - under construction
http://www.merlot.org/merlot/viewMaterial.htm?id=893600
Stage 1 of a ePortfolio for Promising Course Redesign. Page is still under contruction. The page describes an online course for introductory statistics.15.070J Advanced Stochastic Processes (MIT)
http://www.merlot.org/merlot/viewMaterial.htm?id=884047
This class covers the analysis and modeling of stochastic processes. Topics include measure theoretic probability, martingales, filtration, and stopping theorems, elements of large deviations theory, Brownian motion and reflected Brownian motion, stochastic integration and Ito calculus and functional limit theorems. In addition, the class will go over some applications to finance theory, insurance, queueing and inventory models.18.440 Probability and Random Variables (MIT)
http://www.merlot.org/merlot/viewMaterial.htm?id=884379
This course introduces students to probability and random variables. Topics include distribution functions, binomial, geometric, hypergeometric, and Poisson distributions. The other topics covered are uniform, exponential, normal, gamma and beta distributions; conditional probability; Bayes theorem; joint distributions; Chebyshev inequality; law of large numbers; and central limit theorem.