LEADER 03734nam 2200493 450 001 9910537952503321 005 20230731121659.0 010 $a1-119-52839-9 010 $a1-119-52838-0 010 $a1-119-52840-2 035 $a(CKB)4100000007758291 035 $a(Au-PeEL)EBL5724035 035 $a(CaPaEBR)ebr11657958 035 $a(OCoLC)1089395752 035 $a(CaSebORM)9781119528418 035 $a(MiAaPQ)EBC5724035 035 $a(EXLCZ)994100000007758291 100 $a20190322d2019 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aTesting statistical assumptions in research /$fJ. P. Verma, Abdel-Salam G. Abdel-Salam 205 $a1st edition 210 1$aHoboken, NJ :$cWiley,$d2019. 215 $a1 online resource (226 pages) 225 1 $aTHEi Wiley ebooks 311 $a1-119-52841-0 320 $aIncludes bibliographical references and index. 330 $aComprehensively 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. 410 0$aTHEi Wiley ebooks. 606 $aStatistical hypothesis testing 615 0$aStatistical hypothesis testing. 676 $a005.55 700 $aVerma$b J. P.$0782107 702 $aAbdel-Salam$b Abdel-Salam G. 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910537952503321 996 $aTesting statistical assumptions in research$92615401 997 $aUNINA