Bootstrap Methods

The bootstrap is now a vital statistical tool and, due to its power and simplicity, its use is ubiquitous.  Learn more in Dr. Chernick's online course "Bootstrap Methods" at Statistics.com. For more details please visit http://www.statistics.com/bootstrap/.

"Bootstrap Methods" covers the basic theory and application of the bootstrap family of procedures, with the emphasis on applications. After taking this course, participants will be able to use the bootstrap procedure to assess bias and variance, test hypotheses, and produce confidence intervals.  The bootstrap is illustrated also for regression and time series procedures. Basic and improved bootstrap procedures are covered.  The software used is mostly R.

Who Should Take This Course:

Statisticians and data analysts who perform statistical inference, or need to assess uncertainty in their data. Those working with data that does not meet the distributional requirements of standard statistical procedures or with unusual statistics or complex estimators will find the course particularly useful.

Course Program:

Course outline: The course is structured as follows

SESSION 1: Introduction

• Wide range of application
• Historical notes
• Bias estimation
• Efron's patch data example
• Estimating other parameters of a distribution

SESSION 2: Parameter Estimation

• Bias estimation (continued)
• Error rate estimation problems
• Confidence intervals and hypothesis test
• Percentile method confidence intervals
• Higher order bootstrap confidence intervals
• A 1-1 relationship between confidence intervals and hypothesis tests
• Problems with bootstrap confidence intervals for variances

SESSION 3: Regression, Time Series, Which Methods?

• Linear Regression, bootstrap residuals or vectors
• Non-linear Regression
• A Quasi-optical experiment
• Nonparametric Regression
• Cox Model
• CART
• Bootstrap Bagging
• Time Series Analysis
• Model-based vs block resampling
• Bootstrap variants
• Bayesian bootstrap
• Smoothed bootstrap
• Parametric bootstrap
• Iterated bootstrap
• Number of repetitions (replications)

SESSION 4: Special Topics, Bootstrap Failures and Remedies

• Spatial data: kriging
• Subset selection
• Examples of Gong and Gunter
• p-value adjustment
• Process capability indices
• Bioequivalence
• Failure Due to Small Sample Size
• Failure Due to Infinite Moments and Remedy (introducing m-out-of-n bootstrap)
• Failure Due to Estimating Extremes and Remedies

Dr. Michael Chernick and Dr. Robert LaBudde are the coauthors of "Bootstrap Methods with Applications in R," the course text.  Chernick studied with Bradley Efron in the bootstrap's early days, is a Fellow of the American Statistical Association, the 1983 winner of the Wolfowitz Prize, and the author of more than 30 journal articles.  LaBudde is president and founder of Least Cost Formulations, Ltd., a mathematical software development company specializing in optimization and process control software for manufacturing companies.

You will be able to ask questions and exchange comments with Dr. Michael Chernick and Dr. Robert LaBudde via a private discussion board throughout the course.   The courses take place online at statistics.com in a series of 4 weekly lessons and assignments, and require about 15 hours/week.  Participate at your own convenience; there are no set times when you must be online. You have the flexibility to work a bit every day, if that is your preference, or concentrate your work in just a couple of days.

For Indian participants statistics.com accepts registration for its courses at special prices in Indian Rupees through its partner, the Center for eLearning and Training (C-eLT), Pune.

For India Registration and pricing, please visit us at www.india.statistics.com.

Email: info@c-elt.com

Call: 020 66009116

Websites:

www.india.statistics.com

www.c-elt.com

Biostatistics 2

William Weldon, the 19th century British zoologist, was present at the creation of modern biostatistics.  In 1893 he served, with Karl Pearson, on a Royal Committee "For the Purpose of Conducting Statistical Inquiry into the Variability of Organisms."  A year later, he spent considerable time tossing a set of 12 dice more than 26,000 times and recording the results.  Pearson used these data in his paper on the chi-square.

The Institute for Statistics Education at Statistics.com offers courses in a number of topics in biostatistics throughout the year. Statistics.com offers an online courses “Biostatistics 2”. This course covers clinical trial designs including randomized controlled trials, ROC curves, CI and tests for relative risk and odds ratio, and an introduction to survival analysis, and is taught by Dr. Abhaya Indrayan. For more details please visit at http://www.statistics.com/biostat2/.

Who Should Take This Course:

This non-mathematical course is specially designed for medical and health professionals who deal with medical data and want to acquire some statistical skills. These include nursing, pharmacy, laboratory technology and nutrition professionals beside physicians, surgeons and dentists.

Course Program:

Course outline: The course is structured as follows

SESSION 1: Introduction to Designs for Clinical Trials

• Control group
• Randomization and matching
• Blinding and masking
• One-way, two-way and repeated measures designs
• Cross-over design

SESSION 2: ROC Curves

• Review of sensitivity-specificity
• Serial and parallel tests
• ROC curve
• Predictivity-based ROC curve
• Clinical gains from a test

SESSION 3: Relative Risk (RR) and Odds Ratio (OR)

• Definitions and applicability of RR and OR
• CI and test of hypothesis for RR
• CI and test of hypothesis for attributable risk
• CI and test of hypothesis for OR

SESSION 4: Introductory Survival Analysis

• Censored durations and need of special methods
• Life table method
• Kaplan-Meier method

Dr. Abhaya Indrayan, author of "Medical Biostatistics" (3rd ed., CRC Press), has also written a book on medical research methods. He is former Professor and Chair of the Department of Biostatistics and Medical Informatics at Delhi University College of Medical Sciences, Delhi. He has frequently provided biostatistical consultation to the World Health Organization, the World Bank and UNAIDS. Dr Indrayan has delivered the inaugural address at Biostatistics Workshop at Institute of Cytology and Preventive Oncology, NOIDA, been a Guest of Honor at Workshop on Designs and Sample Size at Postgraduate Institute of Medical Sciences and Research, Chandigarh and presented papers in more than 20 international conferences. 

You will be able to ask questions and exchange comments with the Dr. Abhaya Indrayan via a private discussion board throughout the course.   The courses take place online at statistics.com in a series of 4 weekly lessons and assignments, and require about 15 hours/week.  Participate at your own convenience; there are no set times when you must be online. You have the flexibility to work a bit every day, if that is your preference, or concentrate your work in just a couple of days.

For Indian participants statistics.com accepts registration for its courses at special prices in Indian Rupees through its partner, the Center for eLearning and Training (C-eLT), Pune.

For India Registration and pricing, please visit us at www.india.statistics.com.

Email: info@c-elt.com

Call: 020 66009116

Websites:

www.india.statistics.com

www.c-elt.com

Calculus Review

Is your calculus rusty?  Refresh it with “Calculus Review,” which is a refresher in calculus. Calculus at this level concerns itself with three primary concepts: the limit, the derivative and the integral. Applications involving statistics supplement the more traditional calculus examples. Participants will learn how to find and interpret derivatives and integrals, both by hand and via software. Learn “Calculus Review” in Dr. John Verzani’s online course at Statistics.com. For more details please visit at http://www.statistics.com/calculus/.

Course Program:

Course outline: The course is structured as follows

SESSION 1: Calculus Review, Limits, The Derivative

• Pre-Calculus Concepts
• Limits
• Differentiation
• Computer Examples

SESSION 2: Applications of the Derivative, The Integral

• Applications
• Area and the Riemann Sum
• Computer Examples

SESSION 3: Integration

• Fundamental Theorem of Calculus
• Antiderivatives: Evaluation of Indefinite Integrals
• Applications
• Computer Examples

The instructor for "Calculus Review," John Verzani is a member of the faculty at the College of Staten Island of the City University of New York, and the author of "Using R for Introductory Statistics" (CRC Press). His research interests and publications are in the area of superprocesses. 

You will be able to ask questions and exchange comments with the Dr. John Verzani via a private discussion board throughout the course.   The courses take place online at statistics.com in a series of 4 weekly lessons and assignments, and require about 15 hours/week.  Participate at your own convenience; there are no set times when you must be online. You have the flexibility to work a bit every day, if that is your preference, or concentrate your work in just a couple of days.

For Indian participants statistics.com accepts registration for its courses at special prices in Indian Rupees through its partner, the Center for eLearning and Training (C-eLT), Pune.

For India Registration and pricing, please visit us at www.india.statistics.com.

Email: info@c-elt.com

Call: 020 66009116

Websites:

www.india.statistics.com

www.c-elt.com

Environmental Statistics

How do you know if the pH level in a lake is changing?  How should you design a study to determine whether a site has been damaged by mining?  Learn more about the application of statistical methods to environmental problems in Dr. Bryan Manly's online course, "Environmental Statistics," at Statistics.com. For more details please visit at http://www.statistics.com/enviro/.

"Environmental Statistics" is designed for the environmental analyst or scientist with some previous exposure to statistics.  It reviews general statistical procedures (sampling, regression, analysis of variance, control charts) from an environmental science angle, and also covers topics that are specific to environmental impact and risk assessment.

Course Program:

Course outline: The course is structured as follows

SESSION 1: Background and Sampling

• Examples illustrating the role of statistics in environmental science.
• Optional review of basic statistical concepts for those who need it.
• Environmental sampling strategies and the analysis of the data obtained: random sampling, stratified sampling, systematic sampling, ratio estimation, double sampling, choosing sample sizes, the Data Quality Objectives (DQO) process

SESSION 2: Environmental Data Analysis

• Models for data: standard statistical distributions, the linear regression model, analysis of variance, generalized linear models for non-normal data
• Statistical inference: different types of study (observational and experimental), quasi-experiments, design-based and model-based inference, tests of significance and confidence intervals, computer-intensive methods, avoiding pseudoreplication, multiple testing procedures, meta analysis, Bayesian methods
• Using analysis of variance with environmental monitoring data

SESSION 3: Monitoring and Impact Assessment

• Using control charts and CUSUM charts with monitoring data
• Designs and analyses for impact assessment: BACI designs, impact-control designs, before-after designs, impact gradient designs, possible inferences. Assessing site reclamation: problems with usual tests of significance, testing for bioequivalence
• Introduction to time series analysis: components of time series, serial correlation, test for randomness, detection of change points and trend, more complicated time series models.

SESSION 4: Spatial and Censored Data, and Monte Carlo Risk Assessment

• Spatial data analysis: types of spatial data, analysis of count data, randomness in where points are located, the Mantel randomization test for spatial correlation, the geostatistical methods (variograms and kriging), correlation between variables in space
• Censored data: estimation of the population mean and variance from a single sample, estimation of quantiles, comparing the means of two or more samples, regression
• Principles of Monte Carlo risk assessment
• Using Resampling Stats for Excel for risk assessment.

Dr. Bryan Manly is a consultant with Western EcoSystem Technology, Inc. in Cheyenne, Wyoming. Before that, he was Chair of Statistics and Director of the Center for Applications of Statistics and Mathematics at the University of Otago, New Zealand.  Dr. Manly is the author of "Statistics for Environmental Science and Management," "Randomization, Bootstrap and Monte Carlo Methods in Biology," "The Statistics of Natural Selection," "Multivariate Statistical Methods," "Resource Selection by Animals," "The Design and Analysis of Research Studies," and over 200 articles in refereed journals. Participants can ask questions and exchange comments with Dr. Manly via a private discussion board throughout the period.

You will be able to ask questions and exchange comments with the Dr. Bryan Manly via a private discussion board throughout the course.   The courses take place online at statistics.com in a series of 4 weekly lessons and assignments, and require about 15 hours/week.  Participate at your own convenience; there are no set times when you must be online. You have the flexibility to work a bit every day, if that is your preference, or concentrate your work in just a couple of days.

For Indian participants statistics.com accepts registration for its courses at special prices in Indian Rupees through its partner, the Center for eLearning and Training (C-eLT), Pune.

For India Registration and pricing, please visit us at www.india.statistics.com.

Email: info@c-elt.com

Call: 020 66009116

Websites:

www.india.statistics.com

www.c-elt.com

Designing Valid Statistical Studies

Statistical studies gone wrong:  a famous example is the decline in coronary heart disease among women taking hormone replacement therapy (HRT), reported in numerous observational studies.  The effect disappeared in later randomized trials - it was likely due to a third correlated factor (socioeconomic status). 

Learn more about how to design a valid statistical study from the ground up in Dr. David Kleinbaum's and Dr. Mildred Maisonet's online course "Designing Valid Statistical Studies," at Statistics.com. For more details please visit at http://www.statistics.com/validstudies.

"Designing Valid Statistical Studies," by Dr. David Kleinbaum and Dr. Mildred Maisonet, emphasizes the underlying concepts and methods for addressing validity and bias issues in statistical research. Topics covered in the course include: overview of validity and bias, selection bias, information bias, and confounding bias.

Who Should Take This Course:

Researchers who need to design, or review the designs of, statistical studies.

Course Program:

Course outline: The course is structured as follows

SESSION 1: Review Types of Studies, Validity

• Methodologic issues
• Clinical trial (brief overview)
• Observational
• Case-control
• Cross-sectional
• Validity vrs. precision
• Internal vrs. external validity

SESSION 2: Bias and Confounding

• Selection bias (brief overview)
• Information bias (brief overview)
• Confounding

SESSION 3: Controlling Extraneous factors

• At design stage
• At analysis stage
• Randomization
• Matching

SESSION 4: Matching and Stratification

Dr. David Kleinbaum (Emory University) is internationally known for his textbooks in statistical and epidemiologic methods and as an outstanding teacher.  He is the course designer, and the author of "Epidemiologic Research - Principles and Quantitative Methods", "Survival Analysis- A Self Learning Text," and other texts. 

Dr. Mildred Maisonet, who will lead the class discussions in this session of the course, is an Adjunct Assistant Professor at Rollins School of Public Health, Emory University and an Epidemiologist at TKC Integrated Services, LLC.  Participants can ask questions and exchange comments with her via a private discussion board throughout the period.

You will be able to ask questions and exchange comments with the Dr. Mildred Maisonet  and Dr. David Kleinbaum via a private discussion board throughout the course.   The courses take place online at statistics.com in a series of 4 weekly lessons and assignments, and require about 15 hours/week.  Participate at your own convenience; there are no set times when you must be online. You have the flexibility to work a bit every day, if that is your preference, or concentrate your work in just a couple of days.

For Indian participants statistics.com accepts registration for its courses at special prices in Indian Rupees through its partner, the Center for eLearning and Training (C-eLT), Pune.

For India Registration and pricing, please visit us at www.india.statistics.com.

Email: info@c-elt.com

Call: 020 66009116

Websites:

www.india.statistics.com

www.c-elt.com

Sentiment Analysis

Mike Dewar, data scientist at bitly, described sentiment analysis recently as "rubbish," but noted that lots of it is being bought and sold.  Sentiment analysis is the relatively new art and science of distilling useful data from this mass of unstructured text.  If you are engaged in buying or using sentiment analysis, shouldn't you learn something about how it works?  Nitin Indurkhya's online course in Sentiment Analysis is coming up soon. For details please visit at http://www.statistics.com/sentiment-analysis/.

"Sentiment Analysis" introduces you to the algorithms, techniques and software used in sentiment analysis. Their use will be illustrated by reference to existing applications, particularly product reviews and opinion mining. The course will try to make clear both the capabilities and the limitations of these applications. For real-world applications, sentiment analysis draws heavily on work in computational linguistics and text-mining. At the completion of the course, a student will have a good idea of the field of sentiment analysis, the current state-of-the-art and the issues and problems that are likely to be the focus of future systems.

Who Should Take This Course:

Analysts, researchers and managers who deal with, or might need to deal with, Sentiment Analysis systems at a variety of levels - needs assessment, design, deployment and operation.

Course Program:

Course outline: The course is structured as follows

SESSION 1: Introduction and Subjectivity Analysis

• Text Categorization concepts
• Computational Linguistics concepts
• Subjectivity Analysis

SESSION 2: Sentiment Extraction

• Topic Extraction
• Product Reviews
• Sentiment analysis of Comparative Sentences
• Applications

SESSION 3: Opinion Retrieval and Spam

• Searching for Opinions
• Opinion Summarization
• Opinion Spam
• Applications

Nitin Indurkhya is co-author of "Text Mining" (Springer), and co-editor of the "Handbook of Natural Language Processing" (CRC). Dr. Indurkhya is the founder and president of Data-Miner Pty Ltd, an Australian company engaged in data-mining consulting and education, and has served as Principal Research Scientist at eBay and Professor at the School of Computer Science and Engineering, University of New South Wales (Australia).  Participants can ask questions and exchange comments directly with Dr. Indurkhya via a private discussion forum throughout each course.

You will be able to ask questions and exchange comments with the Dr. Nitin Indurkhya via a private discussion board throughout the course.   The courses take place online at statistics.com in a series of 3 weekly lessons and assignments, and require about 15 hours/week.  Participate at your own convenience; there are no set times when you must be online. You have the flexibility to work a bit every day, if that is your preference, or concentrate your work in just a couple of days.

For Indian participants statistics.com accepts registration for its courses at special prices in Indian Rupees through its partner, the Center for eLearning and Training (C-eLT), Pune.

For India Registration and pricing, please visit us at www.india.statistics.com.

Email: info@c-elt.com

Call: 020 66009116

Websites:

www.india.statistics.com

www.c-elt.com