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Introduction to Time Series Analysis and Forecasting
Praise for the First Edition "...[t]he book is great for readers who need to apply the methods and models presented but have little background in mathematics and statistics." -MAA Reviews Thoroughly updated throughout, Introduction to Time Series Analysis and Forecasting, Second Edition presents the underlying theories of time series analysis that are needed to analyze time-oriented data and construct real-world short- to medium-term statistical forecasts. Authored by highly-experienced academics and professionals in engineering statistics, the Second Edition features discussions on both popular and modern time series methodologies as well as an introduction to Bayesian methods in forecastin...
Screening
The process of discovery in science and technology may require investigation of a large number of features, such as factors, genes or molecules. In Screening, statistically designed experiments and analyses of the resulting data sets are used to identify efficiently the few features that determine key properties of the system under study. This book brings together accounts by leading international experts that are essential reading for those working in fields such as industrial quality improvement, engineering research and development, genetic and medical screening, drug discovery, and computer simulation of manufacturing systems or economic models. Our aim is to promote cross-fertilization ...
Introduction to Time Series Analysis and Forecasting
An accessible introduction to the most current thinking in and practicality of forecasting techniques in the context of time-oriented data. Analyzing time-oriented data and forecasting are among the most important problems that analysts face across many fields, ranging from finance and economics to production operations and the natural sciences. As a result, there is a widespread need for large groups of people in a variety of fields to understand the basic concepts of time series analysis and forecasting. Introduction to Time Series Analysis and Forecasting presents the time series analysis branch of applied statistics as the underlying methodology for developing practical forecasts, and it...
Introduction to Statistical Quality Control
"Once solely the domain of engineers, quality control has become a vital business operation used to increase productivity and secure competitive advantage. Introduction to Statistical Quality Control offers a detailed presentation of the modern statistical methods for quality control and improvement. Thorough coverage of statistical process control (SPC) demonstrates the efficacy of statistically-oriented experiments in the context of process characterization, optimization, and acceptance sampling, while examination of the implementation process provides context to real-world applications. Emphasis on Six Sigma DMAIC (Define, Measure, Analyze, Improve and Control) provides a strategic proble...
Gale Researcher Guide for: Economic Forecasting
Gale Researcher Guide for: Economic Forecasting is selected from Gale's academic platform Gale Researcher. These study guides provide peer-reviewed articles that allow students early success in finding scholarly materials and to gain the confidence and vocabulary needed to pursue deeper research.
Business Experiments with R
BUSINESS EXPERIMENTS with R A unique text that simplifies experimental business design and is dedicated to the R language Business Experiments with R offers a guide to, and explores the fundamentals of experimental business designs. The book fills a gap in the literature to provide a text on the topic of business statistics that addresses issues such as small samples, lack of normality, and data confounding. The author—a noted expert on the topic—puts the focus on the A/B tests (and their variants) that are widely used in industry, but not typically covered in business statistics textbooks. The text contains the tools needed to design and analyze two-treatment experiments (i.e., A/B test...
The Effect
Extensive code examples in R, Stata, and Python Chapters on overlooked topics in econometrics classes: heterogeneous treatment effects, simulation and power analysis, new cutting-edge methods, and uncomfortable ignored assumptions An easy-to-read conversational tone Up-to-date coverage of methods with fast-moving literatures like difference-in-differences
Data Science Fundamentals and Practical Approaches
Learn how to process and analysis data using Python Key Features a- The book has theories explained elaborately along with Python code and corresponding output to support the theoretical explanations. The Python codes are provided with step-by-step comments to explain each instruction of the code. a- The book is quite well balanced with programs and illustrative real-case problems. a- The book not only deals with the background mathematics alone or only the programs but also beautifully correlates the background mathematics to the theory and then finally translating it into the programs. a- A rich set of chapter-end exercises are provided, consisting of both short-answer questions and long-a...
