Comprehensively teaches the basics of testing statistical
assumptions in research and the importance in doing so This book
facilitates researchers in checking the assumptions of statistical
tests used in their research by focusing on the importance of
checking assumptions in using statistical methods, showing them how
to check assumptions, and explaining what to do if assumptions are
not met. Testing Statistical Assumptions in Research discusses the
concepts of hypothesis testing and statistical errors in detail, as
well as the concepts of power, sample size, and effect size. It
introduces SPSS functionality and shows how to segregate data, draw
random samples, file split, and create variables automatically. It
then goes on to cover different assumptions required in survey
studies, and the importance of designing surveys in reporting the
efficient findings. The book provides various parametric tests and
the related assumptions and shows the procedures for testing these
assumptions using SPSS software. To motivate readers to use
assumptions, it includes many situations where violation of
assumptions affects the findings. Assumptions required for
different non-parametric tests such as Chi-square, Mann-Whitney,
Kruskal Wallis, and Wilcoxon signed-rank test are also discussed.
Finally, it looks at assumptions in non-parametric correlations,
such as bi-serial correlation, tetrachoric correlation, and phi
coefficient. An excellent reference for graduate students and
research scholars of any discipline in testing assumptions of
statistical tests before using them in their research study Shows
readers the adverse effect of violating the assumptions on findings
by means of various illustrations Describes different assumptions
associated with different statistical tests commonly used by
research scholars Contains examples using SPSS, which helps
facilitate readers to understand the procedure involved in testing
assumptions Looks at commonly used assumptions in statistical
tests, such as z, t and F tests, ANOVA, correlation, and regression
analysis Testing Statistical Assumptions in Research is a valuable
resource for graduate students of any discipline who write thesis
or dissertation for empirical studies in their course works, as
well as for data analysts.
General
Is the information for this product incomplete, wrong or inappropriate?
Let us know about it.
Does this product have an incorrect or missing image?
Send us a new image.
Is this product missing categories?
Add more categories.
Review This Product
No reviews yet - be the first to create one!
Welcome to Loot.co.za!
Sign in / Register |Wishlists & Gift Vouchers |Help | Advanced search
