This website is for an old version of the course, from 2016/17. Informatics 1: Data & Analysis has moved on to new years and new students. Please follow the link below to see the current course pages.
All exam results should now be available through EUCLID. A total of 278 students sat the Inf1-DA exam this year, with over 95% passing and very many achieving Grade A. Those are excellent results, congratulations.
I’ll publish a more detailed feedback report later, with information about student solutions to all of the exam questions. If you have questions or concerns about your result in this or any other course then contact your Personal Tutor to discuss this further.
Continue reading Exam Results
I’ve uploaded reports on the written assignment and on last year’s Inf1-DA exam. These give detailed notes on solutions and discuss the range of answers given by students. You can also find these on the coursework web page and the ITO past paper pages.
Please fill out the short online feedback survey for Inf1-DA. This is organised centrally by the University, with all results sent to the individual course organiser and to the Director of Teaching. I read every comment individually, and for Informatics courses we post results online to help other students choosing courses for the future.
|Feedback for this course:||Informatics 1: Data & Analysis|
|All surveys on MyEd:||Course Enhancement Questionnaires|
|Reports from previous years:||Student Course Feedback|
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 introduced a selection of data scales — refinements of the qualitative/quantitative distinction — and discussed in more detail issues of the application and misapplication of statistics.
Continue reading Lecture 19: Data Scales; Correlation and Causation
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