Learn how to use R 4, write and save R scripts, read in and write out data files, use built-in functions, and understand common statistical methods. This in-depth tutorial includes key R 4 features including a new color palette for charts, an enhanced reference counting system (useful for big data), and new data import settings for text (as well as the statistical methods to model text-based, categorical data).Each chapter starts with a list of learning outcomes and concludes with ...

Carry out a variety of advanced statistical analyses including generalized additive models, mixed effects models, multiple imputation, machine learning, and missing data techniques using R. Each chapter starts with conceptual background information about the techniques, includes multiple examples using R to achieve results, and concludes with a case study.Written by Matt and Joshua F. Wiley, Advanced R Statistical Programming and Data Models shows you how to conduct data a...

Program for data analysis using R and learn practical skills to make your work more efficient. This book covers how to automate running code and the creation of reports to share your results, as well as writing functions and packages. Advanced R is not designed to teach advanced R programming nor to teach the theory behind statistical procedures. Rather, it is designed to be a practical guide moving beyond merely using R to programming in R to automate tasks.This book will...

Program for data analysis using R and learn practical skills to make your work more efficient. This revised book explores how to automate running code and the creation of reports to share your results, as well as writing functions and packages. It includes key R 4 features such as a new color palette for charts, an enhanced reference counting system, and normalization of matrix and array types where matrix objects now formally inherit from the array class, eliminating inconsistencies....

Simplify stats and learn how to graph, analyze, and interpret data the easy wayStatistical Analysis with R For Dummies makes stats approachable by combining clear explanations with practical applications. You'll learn how to download and use R and RStudio—two free, open-source tools—to learn statistics concepts, create graphs, test hypotheses, and draw meaningful conclusions. Get started by learning the basics of statistics and R, calculate descriptive sta...

Data mining is the process of automatically searching large volumes of data for models and patterns using computational techniques from statistics, machine learning and information theory; it is the ideal tool for such an extraction of knowledge. Data mining is usually associated with a business or an organization's need to identify trends and profiles, allowing, for example, retailers to discover patterns on which to base marketing objectives.This book looks at both classical and ...

Build Machine Learning models with a sound statistical understanding.Key FeaturesLearn about the statistics behind powerful predictive models with p-value, ANOVA, and F- statistics.Implement statistical computations programmatically for supervised and unsupervised learning through K-means clustering.Master the statistical aspect of Machine Learning with the help of this example-rich guide to R and Python.Book DescriptionCompl...

This book presents the basic procedures for utilizing SAS Enterprise Guide to analyze statistical data. SAS Enterprise Guide is a graphical user interface (point and click) to the main SAS application. Each chapter contains a brief conceptual overview and then guides the reader through concrete step-by-step examples to complete the analyses. The eleven sections of the book cover a wide range of statistical procedures including descriptive statistics, correlation and simple regression, t te...

The ideal review for your statistics course geared toward engineeringMore than 40 million students have trusted Schaum’s Outlines for their expert knowledge and helpful solved problems. Written by renowned experts in their respective fields, Schaum’s Outlines cover everything from math to science, nursing to language. The main feature for all these books is the solved problems. Step-by-step, authors walk readers through coming up with solutions to exercises in thei...

Explore the big data field and learn how to perform data analytics and predictive modelling in STATA Key FeaturesBook DescriptionSTATA is an integrated software package that provides you with everything you need for data analysis, data management, and graphics. STATA also provides you with a platform to efficiently perform simulation, regression analysis (linear and multiple) \[and custom programming. This book covers data management, graphs visualizat...

Explore effective trading strategies in real-world markets using NumPy, spaCy, pandas, scikit-learn, and KerasKey FeaturesImplement machine learning algorithms to build, train, and validate algorithmic modelsCreate your own algorithmic design process to apply probabilistic machine learning approaches to trading decisionsDevelop neural networks for algorithmic trading to perform time series forecasting and smart analyticsBook Descr...

Understanding Statistics in the Behavioral Sciences is designed to help readers understand research reports, analyze data, and familiarize themselves with the conceptual underpinnings of statistical analyses used in behavioral science literature. The authors review statistics in a way that is intended to reduce anxiety for students who feel intimidated by statistics. Conceptual underpinnings and practical applications are stressed, whereas algebraic derivations and complex formula...