SPSS Survival Manual: A step by step guide to data analysis using SPSSThe SPSS Survival Manual throws a lifeline to students and researchers grappling with the SPSS data analysis software. In this fully revised edition of her bestselling text, Julie Pallant guides you through the entire research process, helping you choose the right data analysis technique for your project. From the formulation of research questions, to the design of the study and analysis of data, to reporting the results, Julie discusses basic and advanced statistical techniques. She outlines each technique clearly, with stepbystep procedures for performing the analysis, a detailed guide to interpreting SPSS output and an example of how to present the results in a report. For both beginners and experienced SPSS users in psychology, education, business, sociology, health and related disciplines, the SPSS Survival Manual is an essential guide. Illustrated with screen grabs, examples of output and tips, it is supported by a website with sample data and guidelines on report writing. In this third edition all chapters have been updated to accommodate changes to SPSS procedures, screens and output. A new flowchart is included for SPSS procedures, and factor analysis procedures have been streamlined. It includes extra examples and material on syntax. Additional datafiles are available on the book's support website. 
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Post Hoc analysisrferencia 2
Contents
1  
Part Two Preparing the data file  25 
Part Three Preliminary analyses  51 
Part Four Statistical techniques to explore relationships among variables  119 
Part Five Statistical techniques to compare groups  201 
Appendix Details of data files  312 
Recommended reading  327 
References  329 
Index  333 
Other editions  View all
SPSS Survival Manual: A step by step guide to data analysis using SPSS Julie Pallant Limited preview  2001 
SPSS Survival Manual: A Step by Step Guide to Data Analysis Using IBM SPSS Julie Pallant Limited preview  2016 
Common terms and phrases
age groups agegp3 analysis of variance ANOVA betweengroups categorical variable Chapter chisquare choose click on Analyze Click on Continue codebook column components consider continuous variable correlation coefficients covariate data file dependent variable dependent variable e.g. Descriptive Statistics dialogue box distribution of scores e.g. total effect size error explore factor analysis Fear of Statistics fost1 Friedman Test graph independent indicate Interpretation of output intervention KruskalWallis Test labelled logistic regression Mahalanobis distance males and females MannWhitney menu multiple regression multivariate Nonparametric alternative normally distributed number of different oneway outliers parametric partial eta squared Paste to save posthoc tests predictor recode relationship research question sample save to Syntax scale scatterplot screen significant difference social desirability SPSS statistical techniques statistically significant Statistics Test survey3ED.sav Syntax Editor ttest Tabachnick and Fidell tick Total PCOISS total perceived stress total score variable e.g. sex variable name Variables box
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Page 254  Tests the null hypothesis that the error covariance matrix of the orthonormalized transformed dependent variables is proportional to an identity matrix. a May be used to adjust the degrees of freedom for the averaged tests of significance. Corrected tests are displayed in the Tests of WithinSubjects Effects table. b Design: Intercept...
Page 234  Levene's Test for \ Equality of Variances \ ttest for Equality of Means \ \ 95% Confidence \ Interval of the Sig.
Page 216  Symmetric Measures a Not assuming the null hypothesis. b Using the asymptotic standard error assuming the null hypothesis.
Page 254  Based on estimated marginal means * The mean difference is significant at the .05 level. a Adjustment for multiple comparisons: Least Significant Difference (equivalent to no adjustments).
Page 260  Tests the null hypothesis that the error variance of the dependent variable is equal across groups. a Design: Intercept+FERTILIZ+FARM Tests of BetweenSubjects Effects Dependent Variable: YIELD a. MS(FARM) b MS(Error) The first table, 'Levene's Test of Equality of Error Variances', would normally contain an estimate of the homogeneity of the variances in each factor combination.
Page 101  A full discussion of this point is beyond the scope of this paper (rather, see Chilman, 1983).
Page 327  Gable, RK, & Wolf, MB (1993). Instrument development in the affective domain: Measuring attitudes and values in corporate and school settings.