What's the Question?: Deciding What You Really Want to Know (Chapman & Hall/CRC Data Science Series) - Image 1

£49.89

Chapman and Hall/CRC What's the Question?: Deciding What You Really Want to Know (Chapman & Hall/CRC Data Science Series)

Name: What's the Question?: Deciding What You Really Want to Know (Chapman & Hall/CRC Data Science Series)
Brand: Chapman and Hall/CRC
Price: 49.89 GBP
Availability: InStock

Computing & Internet

It has never been this cheap. We have no record of a lower price.

£50 today · cheaper than every other day in the last 3 months

NEW HERE?

Amazon shows you one price. We show you all of them.

Tosheroon watches Amazon prices so you don't have to. Every product on Amazon has a price history — we make it visible. Set the price you'd actually pay, and we'll email you the second it gets there. No app, no account, one email.

WHAT'S ON THIS PAGE

↓ Price chart
when this has been cheap or pricey

↓ Forecast
where the price is heading next

↓ Statistics
all-time high & low, recent range

↑ Price alert
name your number, we'll email you

Price History & Forecast

Grey patches = out of stock. Cheaper = lower on the chart. Hover for exact prices.

Last 59 days • 59 data points (No recent data available)

Historical

Generating forecast...

Price Distribution

Price distribution over 59 days • 2 price levels

Days at Price

Current Price

Price Analysis

Most common price: £52 (56 days, 94.9%)

Price range: £50 - £52

Price levels: 2 different prices over 59 days

Product Specifications

Brand: Chapman and Hall/CRC
Format: paperback
ASIN: 1041213565
Category: Books > Subjects > Computing & Internet
Domain: Amazon UK
Release Date: 21 May 2026
Listed Since: 15 November 2025

Barcode

No barcode data available

Chapman and Hall/CRC What's the Question?: Deciding What You Really Want to Know (Chapman & Hall/CRC Data Science Series)

It has never been this cheap. We have no record of a lower price.

Price History & Forecast

Price Distribution

Price Analysis

Product Specifications

Barcode

Similar Products You Might Like

Test-Driven Data Analysis (Chapman & Hall/CRC Data Science Series)

The Art of Data Science: A Practitioner's Guide

Exploratory Data Analysis Using R (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)

Statistical Practice for Data Science: With Hands-On Illustrations Using R

Graduate Students in Data Science Consulting: A Blueprint for Success

Open Science with R (Chapman & Hall/CRC The R Series)

A Course in Large-Sample and High-Dimensional Theory (Chapman & Hall/CRC Texts in Statistical Science)

Introduction to High Performance Computing for Scientists and Engineers, Second Edition (Chapman & Hall/CRC Computational Science)

Principles of Computational Genomics (Chapman & Hall/CRC Computational Biology Series)

High Dimensional Data Analysis: An Interpoint Distance Approach

Introduction to Forestry Data Analysis with R (Chapman & Hall/CRC The R Series)

Bayesian Models in Health Technology Assessment (Chapman & Hall/CRC Biostatistics Series)

Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference (Chapman & Hall/CRC Texts in Statistical Science)

Python for Mathematics (Chapman & Hall/CRC The Python Series)

Logistic Regression: Bridging Theory and Practice

Analysis of Correlated Data with SAS and R, Fifth Edition

Statistics for Biological Networks: How to Infer Networks from Data (Chapman & Hall/CRC Interdisciplinary Statistics)

Sample Surveys in Economics and Finance: A Practical Guide (Chapman and Hall/CRC Series on Statistics in Business and Economics)

R Companion to Epidemiology: Study Design and Data Analysis

Applied Mathematics Toolkit: Modeling, Data, and Algorithms for Scientists and Engineers

Introduction to Machine Learning Algorithms: Basic Principles and Mathematics

Introduction to Python: With Applications in Optimization, Image and Video Processing, and Machine Learning (Chapman & Hall/CRC The Python Series)

Statistical Analytics for Health Data Science with SAS and R (Chapman & Hall/CRC Biostatistics Series)

Monty the Null Hippopotamus: Exploring Statistical Foundations Through Simulation