Price loading...

Foundations of Statistics for Data Scientists: With R and Python (Chapman & Hall/CRC Texts in Statistical Science)

Econometrics

Price data last checked 103 day(s) ago - refreshing...

View at Amazon

Price History & Forecast

No Price Data Available

Price history will appear here once data is collected from Amazon.

Price Distribution

No price data available for histogram

Description

Foundations of Statistics for Data Scientists: With R and Python is designed as a textbook for a one- or two-term introduction to mathematical statistics for students training to become data scientists. It is an in-depth presentation of the topics in statistical science with which any data scientist should be familiar, including probability distributions, descriptive and inferential statistical methods, and linear modeling. The book assumes knowledge of basic calculus, so the presentation can focus on "why it works" as well as "how to do it." Compared to traditional "mathematical statistics" textbooks, however, the book has less emphasis on probability theory and more emphasis on using software to implement statistical methods and to conduct simulations to illustrate key concepts. All statistical analyses in the book use R software, with an appendix showing the same analyses with Python. Key Features: Shows the elements of statistical science that are important for students who plan to become data scientists. Includes Bayesian and regularized fitting of models (e.g., showing an example using the lasso), classification and clustering, and implementing methods with modern software (R and Python). Contains nearly 500 exercises. The book also introduces modern topics that do not normally appear in mathematical statistics texts but are highly relevant for data scientists, such as Bayesian inference, generalized linear models for non-normal responses (e.g., logistic regression and Poisson loglinear models), and regularized model fitting. The nearly 500 exercises are grouped into "Data Analysis and Applications" and "Methods and Concepts." Appendices introduce R and Python and contain solutions for odd-numbered exercises. The book's website (http://stat4ds.rwth-aachen.de/) has expanded R, Python, and Matlab appendices and all data sets from the examples and exercises.

Product Specifications

Format: hardcover
ASIN: 0367748452
Category: Books > Subjects > Business, Finance & Law > Economics > Econometrics
Domain: Amazon UK
Release Date: 30 November 2021
Listed Since: 23 April 2021

Barcode

No barcode data available

Foundations of Statistics for Data Scientists: With R and Python (Chapman & Hall/CRC Texts in Statistical Science)

Price History & Forecast

No Price Data Available

Price Distribution

Description

Product Specifications

Barcode

Similar Products You Might Like

Foundations of Data Science with Python (Chapman & Hall/CRC The Python Series)

Statistical Foundations of Data Science (Chapman & Hall/CRC Data Science Series)

Data Science in R: A Case Studies Approach to Computational Reasoning and Problem Solving (Chapman & Hall/CRC The R Series)

Foundations of Statistical Algorithms: With References to R Packages (Chapman & Hall/CRC Computer Science & Data Analysis)

Probability, Statistics, and Data: A Fresh Approach Using R (Chapman & Hall/CRC Texts in Statistical Science)

Data Science in R: A Case Studies Approach to Computational Reasoning and Problem Solving (Chapman & Hall/CRC: The R Series)

Fundamentals of Causal Inference: With R (Chapman & Hall/CRC Texts in Statistical Science)

Foundations and Applications of Statistics: An Introduction Using R (Pure and Applied Undergraduate Texts)

Introduction to Probability, Statistics & R: Foundations for Data-Based Sciences

Data Science and Machine Learning: Mathematical and Statistical Methods (Chapman & Hall/CRC Machine Learning & Pattern Recognition)

Linear Algebra and Its Applications with R (Textbooks in Mathematics)

Data Science and Machine Learning: Mathematical and Statistical Methods, Second Edition (Chapman & Hall/CRC Machine Learning & Pattern Recognition)

Linear Algebra and Its Applications with R (Textbooks in Mathematics)

Stochastic Modeling and Mathematical Statistics: A Text for Statisticians and Quantitative Scientists (Chapman & Hall/CRC Texts in Statistical Science)

R for Statistics

Computational Statistics: An Introduction to R

Data Science in Practice (Chapman & Hall/CRC Data Science Series)

Data Science Using Python and R (Wiley Series on Methods and Applications in Data Mining)

An Introduction to Statistical Data Science: Theory and Models

Understanding Advanced Statistical Methods (Chapman & Hall/CRC Texts in Statistical Science)

CRC Press Statistics and Data Visualisation with Python Book

Functional Data Analysis with R (Chapman & Hall/CRC Monographs on Statistics and Applied Probability)

An Introduction to R and Python for Data Analysis: A Side-By-Side Approach

Python for R Users: A Data Science Approach