SPSS for applied sciences : basic statistical testing / Cole Davis.

Includes bibliographical references (pages 169-171) and index.

Explains how to use SPSS statistical software, including tests and worked examples.

Part One: Pre-test considerations -- Introduction; What this book does; The organisation of content; Data sets and additional information; How to use this book -- Descriptive and inferential statistics introduced; Descriptive statistics; Inferential statistics -- Parametric and non-parametric tests; Different types of data; Parametric versus non-parametric data -- Using SPSS; Data entry in spreadsheet formats; Data entry with SPSS -- Practical research; Data analysis in context; Notes on research design; A suggestion for data analysis structure; Selecting cases; Other data manipulation techniques.

Part Two: Using the Statistical Tests -- Experiments and quasi-experiments; The analysis of differences; Unrelated and related design; Two or more conditions; Data type; Research design terminology; Different subjects, two conditions; Different subjects, more than two conditions; Same subjects, two conditions; Same subjects, more than two conditions; Factorial ANOVA; Reading factorial ANOVA charts; Multiple comparisons -- Frequency of observations; Dichotomies: the binomial test; Repeated dichotomies: the McNemar test; More than two conditions: Chi-square goodness of fit test; Customising expected values: Chi-square goodness of fit; Relationships between variables: Chi-square test of association -- The time until events; Statistical assumptions; The Kaplan-Meier survival function; The life table -- Correlations, regression and factor analysis; Correlation; Regression; Partial correlation: 'partialling out'; The multiple correlation matrix; Factor analysis: a data reduction methodology.

Part Three: Miscellaneous -- Exercises; Questions; Answers -- Reporting in applied settings; Raw data or central tendency?; Charts; Written reporting; Verbal reporting -- Advanced statistical techniques: a taster; MANOVA; Cluster analysis; Logistic regression; Cox's regression (aka the Cox model); Some thoughts on ANCOVA.

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