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Quantitative Analysis: Relationships between variables. Sebastian M. Rasinger Quantitative Research in Linguistics. An Introduction 2 nd edition. 2013. London: Bloomsbury. Relationships between variables. Are the two variables X and Y related in any way?
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Quantitative Analysis:Relationships between variables Sebastian M. Rasinger Quantitative Research in Linguistics. An Introduction 2nd edition. 2013. London: Bloomsbury S.M.Rasinger. 2013. Quantitative Research in Linguistics. 2e. Bloomsbury.
Relationships between variables • Are the two variables X and Y related in any way? • Is learner’s age related to their language learning? • Are younger learners better learners? S.M.Rasinger. 2013. Quantitative Research in Linguistics. 2e. Bloomsbury.
Causal relationships Causal relationships must fulfil 3 criteria: • X and Y must correlate • There is a chronological order between X and Y, e.g. Y follows X or X follows Y • The relationship between X and Y does not disappear when controlling for third variables S.M.Rasinger. 2013. Quantitative Research in Linguistics. 2e. Bloomsbury.
Causal relationships (2) • Example: Age-effect on learner’s L2 attainment – possible 3rd variables • Lengths of residence • Exposure, integration/assimilation • Motivation • (general cognitive abilities) S.M.Rasinger. 2013. Quantitative Research in Linguistics. 2e. Bloomsbury.
Pearson Correlation • Statistical instrument to see whether 2 variables correlate • NO information about causality!!!! • EXCEL: =correl(array1, array2) • -1 ≤ 0 ≤ 1 • 1 = perfect positive correlation: with every unit increase of X, 1 unit increase of Y • -1: perfect negative correlation. With every increase in X, 1 unit decrease in Y S.M.Rasinger. 2013. Quantitative Research in Linguistics. 2e. Bloomsbury.
Example: Correlation Correlation coefficient R=0.133 S.M.Rasinger. 2013. Quantitative Research in Linguistics. 2e. Bloomsbury.
Correlation example (2) S.M.Rasinger. 2013. Quantitative Research in Linguistics. 2e. Bloomsbury.
For non-parametric data • Spearman rank correlation: • -1<rho<1 • Uses ranks instead of actual values • Loss of detail • Kendall’s tau • -1<tau<1 • Good for very small data sets S.M.Rasinger. 2013. Quantitative Research in Linguistics. 2e. Bloomsbury.