My Account Log in

1 option

Statistics for Data Scientists : An Introduction to Probability, Statistics, and Data Analysis / by Maurits Kaptein, Edwin van den Heuvel.

SpringerLink Books Computer Science (2011-2024) Available online

View online
Format:
Book
Author/Creator:
Kaptein, Maurits, Author.
van den Heuvel, Edwin., Author.
Contributor:
SpringerLink (Online service)
Series:
Computer Science (SpringerNature-11645)
Undergraduate topics in computer science 2197-1781
Undergraduate Topics in Computer Science, 2197-1781
Language:
English
Subjects (All):
Computer science-Mathematics.
Mathematical statistics.
Statistics.
Probabilities.
Probability and Statistics in Computer Science.
Statistical Theory and Methods.
Probability Theory.
Local Subjects:
Probability and Statistics in Computer Science.
Statistical Theory and Methods.
Probability Theory.
Physical Description:
1 online resource (XXIV, 321 pages) : 53 illustrations, 19 illustrations in color.
Edition:
1st ed. 2022.
Contained In:
Springer Nature eBook
Place of Publication:
Cham : Springer International Publishing : Imprint: Springer, 2022.
System Details:
text file PDF
Summary:
This book provides an undergraduate introduction to analysing data for data science, computer science, and quantitative social science students. It uniquely combines a hands-on approach to data analysis - supported by numerous real data examples and reusable [R] code - with a rigorous treatment of probability and statistical principles. Where contemporary undergraduate textbooks in probability theory or statistics often miss applications and an introductory treatment of modern methods (bootstrapping, Bayes, et cetera), and where applied data analysis books often miss a rigorous theoretical treatment, this book provides an accessible but thorough introduction into data analysis, using statistical methods combining the two viewpoints. The book further focuses on methods for dealing with large data-sets and streaming-data and hence provides a single-course introduction of statistical methods for data science.
Contents:
1 A First Look at Data
2 Sampling Plans and Estimates
3 Probability Theory
4 Random Variables and Distributions
5 Estimation
6 Multiple Random Variables
7 Making Decisions in Uncertainty
8 Bayesian Statistics.
Other Format:
Printed edition:
ISBN:
978-3-030-10531-0
9783030105310
Access Restriction:
Restricted for use by site license.

The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.

Find

Home Release notes

My Account

Shelf Request an item Bookmarks Fines and fees Settings

Guides

Using the Find catalog Using Articles+ Using your account