Data analysis : an introduction / Michael S. Lewis-Beck.

Includes bibliographical references (page 75).

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This accessible introduction to data analysis focuses on the interpretation of statistical results, in particular those which come from nonexperimental social research. It will provide social science researchers with the tools necessary to select and evaluate statistical tests appropriate for their research question.

1. Introduction -- 2. Data gathering -- The research question -- The sample -- The measures -- Data coding, entry, and checking -- 3. Univariate statistics -- Central tendency -- Dispersion -- Central tendency, dispersion, and outliers -- 4. Measures of association -- Correlation -- Ordinal data: the Tau measure of association -- Nominal data: Goodman and Kruskals' lambda -- Dichotomous variables: flexibility of choice -- Summary and conclusion -- 5. Significance testing -- The logic: a simple example -- Applying the logic: bivariate measures of association -- Summary and conclusion -- 6. Simple regression -- Y as a function of X -- The lease squares principle -- Intercept and slope -- Prediction and goodness-of-fit -- Significance tests and confidence intervals -- Presenting regression results: a summary guide -- 7. Multiple regression -- An example -- The notion of statistical control -- Specification error -- Dummy variables -- Collinearity -- Interaction effects -- Nonlinearity -- Summary and conclusion.

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