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NICOLA BRACE

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Redna cena 29,97 €
Znižana cena 29,97 € Redna cena
Akcija Razprodano

Status dobavljivosti: Na zalogi pri dobavitelju

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ISBN

9780230594593

Mladinska knjiga ID

393122

Leto izida

2009

Datum izida

30.05.2009

Velikost (šxdxv)

150 × 200 × 10

Status dobavljivosti

Na zalogi pri dobavitelju

Jezik

ANG

Teža

300 g

Založnik

PALGRAVE

Avtor

NICOLA BRACE

Opis

Guiding readers through the latest SPSS package (also known as PASW Statistics), the authors provide clear step-by-step instructions on the main statistical techniques, with expanded sections on graphing and exploring data. The new, fully updated edition of this bestseller, now in colour, remains an essential tool for all psychology students.The new edition of this bestselling guide to SPSS (also known as PASW Statistics) is the ideal companion for students learning how to use SPSS to analyse psychological data. As with previous editions, the book retains the comprehensive coverage, clarity and flexibility that has made it an indispensable resource for students at all levels. This 4th Edition: / covers SPSS versions 16 and 17 and is backward compatible with other versions / focuses specifically on the needs of psychologists and psychology students / features a new colour layout and chapter tabs for easy reading and navigation / displays annotated screenshots and key 'tip' boxes to help students track their progress and avoid common pitfalls / provides expanded coverage of graphing and guides students through reporting the outcome of statistical analysis / sets SPSS in the context of research design and statistics, and discusses the rationale and use of each test throughout In addition, a number of sample exercises, datasets and other useful information are available on the Companion Website, to support the text. Please see https://www.palgrave.com/psychology/braceIntroduction Data Entry in SPSS Exploring Data in SPSS Data Handling Tests of Difference for Two Sample Designs Tests of Correlation Tests for Nominal Data Analysis of Variance Multiple Regression Analysis of Covariance and Multivariate Analysis of Variance Discriminant Analysis and Logistic Regression Factor Analysis, and Reliability and Dimensionality of Scales Beyond the Basics

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