Numbers, Hypotheses & Conclusions: A Course in Statistics for the Social Sciences
A tutorial-based programme that addresses some of the problems involved in teaching statistics to undergraduate social science students. It emphasises contemporary approaches to data analysis, the role of statistics in sampling, and the idea that inference depends upon how sampling is conducted.
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Numbers variables and measures
Probability and theoretical distributions 70
The standard normal distribution
The sampling distribution of the mean
Factorial analysis of variance
Repeated measures analysis of variance
Mathematics and Software Support
The logic of analysis of variance
Oneway analysis of variance
Activity allows analysis ANOVA answer assumptions average calculate cell coefficient column conduct consider correct correlation dataset decide defined dependent designs determine dialog divided effect equal equation error estimate example expected factor Figure formula frequency given graph Help important increase independent variable indicate individual interpret interval known mean measures methods multiple normal distribution null hypothesis option output particular points population positive possible prediction present probability problem procedure proportion provides question range rank refer regression reject relationship repeated measures reported represent require response sample mean sampling distribution scale scores shown shows significant simple social SPSS squares standard deviation statistical Step subjects t-test Table tion tutorial Type variables variance variation window z-score