Advanced Quantitative Data Analysis
There are a variety of statistical techniques used to analyse quantitative data that masters students, advanced undergraduates and researchers in the social sciences are expected to be able to understand and undertake. This book explains these techniques, when it is appropriate to use them, how to carry them out and how to write up the results.
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Chapter 01 Introduction
Part 01 Grouping quantitative variables together
Part 02 Explaining the variance of a quantitative variable
Part 03 Sequencing the relationships between three or more quantitative variables
Part 04 Explaining the probability of a dichotomous variable
Part 05 Testing differences between group means
Part 06 Discriminating between groups
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analysis of covariance analysis of variance box in Box button to put calculated Chapter child’s ability child’s academic achievement child’s interest cluster analysis column criterion Data Editor degrees of freedom dependent variable dialog box differ signiﬁcantly discriminant analysis discriminant function dummy variables error example expected frequencies F ratio F-test factor analysis ﬁrst ﬁt Group mean identiﬁed interaction interest and academic Levene’s test likelihood ratio chi-square LISREL output log likelihood logistic regression marital status mean square method multiple regression never married number of groups number of predictors one-way analysis parameters parents partial correlation partial regression coefﬁcient path analysis path coefﬁcients path diagram predictor variables proportion of variance quantitative variables regression analysis sample score statistic shown in Table SPSS output squared multiple correlation standardized partial regression statistically signiﬁcant step structural equation modelling sub-dialog box sum of squares teachers third model two-factor model two-tailed unrelated unstandardized variance in academic within-groups