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

Designing Experiments and Analyzing Data (A Model Comparison Perspective, Third Edition) - 9780367202644

List Price: $65.99
SKU:
9780367202644
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:
    Scott E. Maxwell, Harold D. Delaney, Ken Kelley
    Format:
    Paperback
    Pages:
    1080
    Publisher:
    Taylor & Francis (December 6, 2024)
    Language:
    English
    ISBN-13:
    9780367202644
    Dimensions:
    7" x 10"
    File:
    TAYLORFRANCIS-TayFran_260408044115339-20260408.xml
    Folder:
    TAYLORFRANCIS
    List Price:
    $65.99
    Country of Origin:
    United States
    Pub Discount:
    30
    As low as:
    $62.69
    Publisher Identifier:
    P-CRC
    Discount Code:
    H
    Audience:
    College/higher education
    Weight:
    70.625oz
    Imprint:
    Routledge
    Case Pack:
    1
  • Overview

    The pedagogical approach used throughout the book enables readers to gain an overview of experimental design, from conceptualization of the research question to analysis of the data. Ideal for students and researchers.