INF2FDS: Revision
Revision resources and advice
Here are resources for revision:
 Comprehension questions on Learn.
 Mock test on Learn in Revision folder.
 The workshop sheets and solutions, from week 4 and 6, which have exercises on sampling, confidence intervals, logistic regression, A/B testing and hypothesis testing.
 If you would like more practice, similar to the workshop sheets, there are exercises at the end of each chapter of Modern Mathematical Statistics with Applications  the oddnumbered exercises have answers.
 For extra practice some of the quizzes here may be helpful: https://www.cliffsnotes.com/studyguides/statistics/statisticsquizzes/statisticsquizzes Though you may find some things not on our syllabus, and it may be that they use slightly different terminology.
 We will be monitoring Piazza regularly up until the class test.
Here are our suggestions for revision:
 Revise the notes you took in lectures
 Reread the lecture notes, perhaps taking notes
 Do the sets of comprehension questions available in most topics. For some of the questions there are solutions.
 Look at the summary resource (below), that tries to link together the various aspects of the course up to the end of S1 Week 9.
 Do the questions from the S2 Week 4 and Week 6 workshop sheets.
 Do the mock test on Learn.
 Ask questions on Piazza, and do try to answer each other's questions, which is a valuable way of revising. We will leave posts for around a day to allow time for the students’ answer to develop, and then either endorse or expand on the answer.
Summary resource: overview of FDS S1 Weeks 1 to 9
This table relates the content we've covered in S1 week 19 to the data science process introduced in the Week 1 lectures. We've organised the material in to three aspects: methods, ethics and decisions that you need to make as a data scientist. This table is not definitive and it won't be examined  it's one way of looking at the material.
Data Science process  Methods  Ethics  Decisions 
Ask an interesting question 
 Will answering the question affect individuals or groups


Get the data 



Explore the data 



Model the data 



Communicate and visualise the results 



License
All rights reserved The University of Edinburgh