Radical Brewing: Recipes, Tales and World-Altering Meditations in a Glass
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Radical Brewing takes a hip and creative look at beer brewing, presented with a graphically appealing two-color layout.
included and then with case 30 deleted. The results are summarized in Table 7.1, which shows: (1) the parameters for the regression model when the extreme case is included or excluded; (2) the resulting regression equations; and (3) the value of Y predicted from participant 30’s score on the X variable (which is obtained by replacing the X in the regression equation with participant 30’s score for X, which was 1). Table 7.1 The difference in the parameters of the regression model when one case
ANCOVA. To access these we again need to load the WRS package (see section 5.8.4.). There are two functions that we will look at which can be used to compare trimmed means between two groups including a covariate: ancova() and ancboot(). These methods all work on the same principle. To free the analysis from the restrictions of homogeneity of regression slopes, as well as the other distributional assumptions, these tests compare trimmed means at different points along the covariate. In other
us the variance between individuals within a particular group, and so is an estimate of individual differences within a particular group. Therefore, to get the total value of individual differences we have to calculate the sum of squares within each group and then add them up: This is all well and good when we have different people in each group, but in repeated-measures designs we’ve subjected people to more than one experimental condition, and, therefore, we’re interested in the variation
factors, factor analysis achieves parsimony by explaining the maximum amount of common variance in a correlation matrix using the smallest number of explanatory constructs. There are numerous examples of the use of factor analysis in the social sciences. The trait theorists in psychology used factor analysis endlessly to assess personality traits. Most readers will be familiar with the extroversion-introversion and neuroticism traits measured by Eysenck (1953). Most other personality
total SSCP matrix (T), 707–9 univariate ANOVA for DV 1, 703–4 univariate ANOVA for DV 2, 704–5 uses, 697 multivariate tests, 697 Muris, P. et al, 490, 497 musical tastes: two-way ANOVA, 547 Myers, R., 276 Nagelkerke, N.J.D., 318 Namboodiri, K., 711 nested variables, 856 Neyman, Jerzy, 52, 210 Nichols, L. and Nicki, R., 797, 811 nominal variables, 8, 11 non-parametric tests Friedman’s ANOVA, 686–92 Jonckheere-Tepstra test, 684–6 Kruskal-Wallis test, 674–84 packages, 655, 693