Practical Statistics for Data Scientists 50+ Essential Concepts Using R and Python (Record no. 814545)

MARC details
000 -LEADER
fixed length control field 02334nam a22002777a 4500
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 240125s2020 |||||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781492072942
022 ## - INTERNATIONAL STANDARD SERIAL NUMBER
ISSN-L 9781492072942
041 ## - LANGUAGE CODE
Language code of text/sound track or separate title English
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 001.422
Item number BRU
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Bruce, Peter
9 (RLIN) 879376
Relator term author
245 ## - TITLE STATEMENT
Title Practical Statistics for Data Scientists 50+ Essential Concepts Using R and Python
250 ## - EDITION STATEMENT
Edition statement 2nd
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Beijing :
Name of publisher, distributor, etc. O'Reilly
Date of publication, distribution, etc. c2020
300 ## - PHYSICAL DESCRIPTION
Extent xvi, 342 p.
Other physical details : ill
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc. note Includes Bibliographical References and Index
520 ## - SUMMARY, ETC.
Summary, etc. SUMMARY<br/><br/>Statistical methods are a key part of data science, yet few data scientists have formal statistical training. Courses and books on basic statistics rarely cover the topic from a data science perspective. The second edition of this popular guide adds comprehensive examples in Python, provides practical guidance on applying statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what’s important and what’s not. Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R or Python programming languages and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format. With this book, you’ll learn: Why exploratory data analysis is a key preliminary step in data science How random sampling can reduce bias and yield a higher-quality dataset, even with big data How the principles of experimental design yield definitive answers to questions How to use regression to estimate outcomes and detect anomalies Key classification techniques for predicting which categories a record belongs to Statistical machine learning methods that "learn" from data Unsupervised learning methods for extracting meaning from unlabeled data
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
9 (RLIN) 880292
Topical term or geographic name entry element Mathematical Analysis Statistical Methods
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
9 (RLIN) 880293
Topical term or geographic name entry element Quantitative Research Statistical Methods
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
9 (RLIN) 152545
Topical term or geographic name entry element R Computer Program Language
700 ## - ADDED ENTRY--PERSONAL NAME
Relator term author
Personal name Bruce, Andrew
9 (RLIN) 880294
700 ## - ADDED ENTRY--PERSONAL NAME
Relator term author
Personal name Gedeck, Peter
9 (RLIN) 880295
856 ## - ELECTRONIC LOCATION AND ACCESS
Link text TOC
Uniform Resource Identifier <a href="https://eaklibrary.neduet.edu.pk:8443/catalog/bk/books/toc/9781492072942.pdf">https://eaklibrary.neduet.edu.pk:8443/catalog/bk/books/toc/9781492072942.pdf</a>
856 ## - ELECTRONIC LOCATION AND ACCESS
Link text WEB LINK
Uniform Resource Identifier <a href="https://www.vitalsource.com/en-uk/products/practical-statistics-for-data-scientists-peter-bruce-andrew-bruce-v9781492072898">https://www.vitalsource.com/en-uk/products/practical-statistics-for-data-scientists-peter-bruce-andrew-bruce-v9781492072898</a>
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type Book
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Physical Form Damaged status Not for loan Purchased by Department/Discipline Home library Current library Shelving location Date acquired Source of acquisition Stock Type Cost, normal purchase price Total Checkouts Full call number Barcode Date last seen Budget Year Cost, replacement price Accession Date Koha item type
    Dewey Decimal Classification Text, Paperback     Department of Software Engineering Reference Section Reference Section Reference Section 23/01/2024 38 Purchased 20318.73   001.422 BRU 98602 23/01/2024 2023-24 20318.72 23/01/2024 Reference Collection