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In this final lecture I reviewed two questions from last year’s exams: one on entity-relationship modelling and database queries; and another on statistics and hypothesis testing. The slides give details of the questions and some possible answers, with notes on which elements are important in preparing a solution.
Today’s lecture revisited the idea of correlation in data sets, and introduced the method of hypothesis testing for identifying whether features observed in samples in fact arise by chance.
For paired series of numerical data we can use the correlation coefficient, and for qualitative data the χ2 statistic. The lecture included examples of this applied to last year’s Inf1-DA exam results, bigram frequency in the British National Corpus, and possible gender bias in student admissions to Berkeley in 1973. Continue reading Lecture 18: Hypothesis Testing and chi²→
This morning’s lecture gave a general overview of statistics and their role in analysing quantities of data. Most of the technical constructions — mean, median, mode, standard deviation — are probably familiar to many, but the setting for their application and the computational context may not be. Continue reading Lecture 17: Summary Statistics→