null
Loading... Please wait...
FREE SHIPPING on All Unbranded Items LEARN MORE
Print This Page

Mastering Health Data Science Using R

List Price: $97.99
SKU:
9781032729930
Quantity:
Minimum Purchase
25 unit(s)
  • Availability: Confirm prior to ordering
  • Branding: minimum 50 pieces (add’l costs below)
  • Check Freight Rates (branded products only)

Branding Options (v), Availability & Lead Times

  • 1-Color Imprint: $2.00 ea.
  • Promo-Page Insert: $2.50 ea. (full-color printed, single-sided page)
  • Belly-Band Wrap: $2.50 ea. (full-color printed)
  • Set-Up Charge: $45 per decoration
FULL DETAILS
  • Availability: Product availability changes daily, so please confirm your quantity is available prior to placing an order.
  • Branded Products: allow 10 business days from proof approval for production. Branding options may be limited or unavailable based on product design or cover artwork.
  • Unbranded Products: allow 3-5 business days for shipping. All Unbranded items receive FREE ground shipping in the US. Inquire for international shipping.
  • RETURNS/CANCELLATIONS: All orders, branded or unbranded, are NON-CANCELLABLE and NON-RETURNABLE once a purchase order has been received.
  • Product Details

    Author:
    Alice Paul
    Format:
    Paperback
    Pages:
    372
    Publisher:
    CRC Press (July 21, 2025)
    Imprint:
    Chapman and Hall/CRC
    Language:
    English
    Audience:
    College/higher education
    ISBN-13:
    9781032729930
    Weight:
    24.375oz
    Dimensions:
    6.125" x 9.1875"
    File:
    TAYLORFRANCIS-TayFran_260607043202281-20260607.xml
    Folder:
    TAYLORFRANCIS
    List Price:
    $97.99
    Country of Origin:
    United States
    Pub Discount:
    30
    Case Pack:
    1
    As low as:
    $93.09
    Publisher Identifier:
    P-CRC
    Discount Code:
    H
  • Overview

    This book provides a practical, application-driven guide to using R for public health and health data science, accessible to both beginners and those with some coding experience. Each module starts with data as the driver of analysis before introducing and breaking down the programming concepts needed to tackle the analysis.