1.

Record Nr.

UNINA9910141297003321

Autore

Hoerl Roger Wesley

Titolo

Statistical thinking [[electronic resource] ] : improving business performance / / Roger Hoerl and Ron Snee

Pubbl/distr/stampa

Hoboken, N.J., : John Wiley & Sons, 2012

ISBN

1-118-23685-8

1-119-20272-8

1-280-59156-0

9786613621399

1-118-22338-1

Edizione

[2nd ed.]

Descrizione fisica

1 online resource (543 p.)

Collana

Wiley & SAS business series

Classificazione

BUS061000

Altri autori (Persone)

SneeRonald D

Disciplina

658.4/033

Soggetti

Commercial statistics

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references and index.

Nota di contenuto

pt. 1. Statistical thinking concepts -- pt. 2. Statistical engineering : frameworks and basic tools -- pt. 3. Formal statistical methods.

Sommario/riassunto

"How statistical thinking and methodology can help you make crucial business decisions. Straightforward and insightful, Statistical Thinking: Improving Business Performance, Second Edition, prepares you for business leadership by developing your capacity to apply statistical thinking to improve business processes. Unique and compelling, this book shows you how to derive actionable conclusions from data analysis, solve real problems, and improve real processes. Here, you'll discover how to implement statistical thinking and methodology in your work to improve business performance. Explores why statistical thinking is necessary and helpful. Provides case studies that illustrate how to integrate several statistical tools into the decision-making process. Facilitates and encourages an experiential learning environment to enable you to apply material to actual problems. With an in-depth discussion of JMP software, the new edition of this important book focuses on skills to improve business processes, including collecting data appropriate for a specified purpose, recognizing limitations in existing data, and understanding the



limitations of statistical analyses"--