Nursing Research - Quick Guide to Bivariate Statistical Tests - Eleventh Edition

Aug 6, 2026

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Quick Guide to Bivariate Statistical Tests provides a concise decision map for selecting statistical procedures based on the level of measurement of the dependent variable and the type of group comparison (independent versus dependent groups) or correlational analysis. It links nominal, ordinal, and interval/ratio outcomes to commonly used tests such as Fisher’s exact test, McNemar’s test, Mann-Whitney, Wilcoxon signed ranks, Kruskal-Wallis, Friedman’s test, Spearman’s rho, Pearson’s r, and corresponding ANOVA and repeated-measures ANOVA options. It also notes nonparametric alternatives for markedly nonnormal distributions or small samples, supporting evidence-based nursing practice.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages862

Reading Time36 h 12 min

AccessFree to download

Quick Guide to Bivariate Statistical Tests

Group comparisons: independent vs dependent groups

Correlational analyses (relationship strength)

Quick Guide to Bivariate Statistical Tests | Level of measurement
of dependent variable | Group Comparisons:
Number of groups (the independent variable) | | | | Correlational
analyses
(To examine
relationship
strength) | | --- | --- | --- | --- | --- | --- | | | 2 Groups | | 3+ Groups | | | | | Independent
Groups Tests | Dependent Groups Tests | Independent
Groups Tests | Dependent Groups Tests | | | Nominal (Categorical) |

p. 401
(or Fisher’s
exact test)
p. 402 | McNemar”s
test
p. 402 |
p. 401 | Cochran’s Q | Phi coefficient (dichotomous) or Cramér’s V (not restricted to dichotomous)
p. 403 | | Ordinal
(Rank) | Mann-Whitney
Test
p. 396 | Wilcoxon
signed ranks
test
p. 396 | Kruskal
Wallis H test
p. 400 | Friedman’s
test
p. 400 | Spearman’s rho (or Kendall’stau) pp. 403 | | Interval or Ratio (Continuous)* | Independent
group t test
pp. 394-395 | Paired
t test
p. 396 | ANOVA
pp. 396-399 | RM
ANOVA
pp. 400 | Pearson’s r
p. 402 | | | Multifactor ANOVA for 2+ independent variables p. 398 | | | | | | | RM-ANOVA for 2+ groups x 2+ measurements over time p. 424 | | | | | *For distributions that are markedly nonnormal or samples that are small, the nonparametric tests in the row above (for ordinal measures) may be needed. South Asian Edition of NURSING RESEARCH Generating and Assessing Evidence for Nursing Practice 11th Edition Denise F. Polit, PhD, FAAN President Humanalysis, Inc. Saratoga Springs, New York, and Adjunct Professor Griffith University School of Nursing Brisbane, Australia ([www.denisepolit.com](www.denisepolit.com)) Cheryl Tatano Beck, DNSc, CNM, FAAN Distinguished Professor School of Nursing University of Connecticut Storrs, Connecticut Eleventh Edition Copyright © 2021 Wolters Kluwer. Copyright © 2017 Wolters Kluwer. Copyright © 2012 Wolters Kluwer Health | Lippincott Williams & Wilkins. Copyright © 2008, 2004, 1999 by Lippincott Williams & Wilkins. Copyright © 1995, 1991, 1987, 1983, 1978 by J. B. Lippincott Company. All rights reserved. This book is protected by copyright. No part of this book may be reproduced or transmitted in any form or by any means, including as photocopies or scanned-in or other electronic copies, or utilized by any information storage and retrieval system without written permission from the copyright owner, except for brief quotations embodied in critical articles and reviews. Materials appearing in this book prepared by individuals as part of their official duties as US government employees are not covered by the abovementioned copyright. To request permission, please contact Wolters Kluwer at Two Commerce Square, 2001 Market Street, Philadelphia, PA 19103, [via email at permissions@lww.com](via email at permissions@lww.com), or via our website at [shop.lww.com](shop.lww.com) (products and services). IN/0520 This work is provided “as is,” and the publisher disclaims any and all warranties, express or implied, including any warranties as to accuracy, comprehensiveness, or currency of the content of this work. This work is no substitute for individual patient assessment based upon healthcare professionals’ examination of each patient and consideration of, among other things, age, weight, gender, current or prior medical conditions, medication history, laboratory data, and other factors unique to the patient. The publisher does not provide medical advice or guidance, and this work is merely a reference tool. Healthcare professionals, and not the publisher, are solely responsible for the use of this work including all medical judgments and for any resulting diagnosis and treatments. Given continuous, rapid advances in medical science and health information, independent professional verification of medical diagnoses, indications, appropriate pharmaceutical selections and dosages, and treatment options should be made, and healthcar

FAQs

How do you choose a bivariate statistical test based on the dependent variable’s measurement level?

Select the test by matching nominal, ordinal, or interval/ratio measurement of the dependent variable, then use the appropriate procedure for the study type (independent groups, dependent groups, or correlation).

Which tests are recommended for nominal (categorical) outcomes?

For nominal outcomes, the guide lists Fisher’s exact test or p.401–402 options, McNemar’s test for dependent dichotomous groups, Cochran’s Q for 3+ related groups, and association measures such as Phi coefficient or Cramér’s V for correlational analyses.

When should nonparametric tests be used instead of parametric tests?

Nonparametric tests may be needed for markedly nonnormal distributions or when samples are small, as indicated for the row covering ordinal measures.

Aug 6, 2026

Uploaded by Theodora