Case Studies M.Sc. in Applied Statistics
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Transcript of Case Studies M.Sc. in Applied Statistics
Case StudiesM.Sc. in Applied Statistics
Dr. Órlaith BurkeMichaelmas Term 2013
Linear ModelsM.Sc. in Applied Statistics
Dr. Órlaith BurkeMichaelmas Term 2013
AutocorrelationM.Sc. in Applied Statistics
Dr. Órlaith BurkeMichaelmas Term 2013
Statistical MethodsM.Sc. in Applied Statistics
Statistical MethodsM.Sc. in Applied Statistics
Hard work
Statistical MethodsM.Sc. in Applied Statistics
Hard work = Stay engaged
Statistical MethodsM.Sc. in Applied Statistics
Hard work = Stay engagedResponsibility
Statistical MethodsM.Sc. in Applied Statistics
Hard work = Stay engagedResponsibility = Ownership
Statistical MethodsM.Sc. in Applied Statistics
Hard work = Stay engagedResponsibility = Ownership
Read
Statistical MethodsM.Sc. in Applied Statistics
Hard work = Stay engagedResponsibility = Ownership
Read = Read
Case Studies
‘Other’ skillsTransferable skills
Case Studies
Presentation skills
Case Studies
Presentation skillsGroupwork
Case Studies
Presentation skillsGroupwork
Critical Thinking
Case Studies
Presentation skillsGroupwork
Critical ThinkingSynthesis of Ideas
Case Studieso Logisticso Aims of the courseo Taskso Structure of the Lectureso Presentation typeso Feedback o Personal Reflectiono Groups: Allocation, tasks and group work
Logistics
11 am Friday morning Lecture Room in SPR1Week 1-6 MT
10.30am Weeks 7-8 MTNo lecture in Week 2
Lecture Room also available 10.30-11am on Friday mornings for
presenting groups to SET UP and practise before the session that day.
Please note that lectures will start promptly on time!
Material available on WebLearn
Online Material
Aims of the courseTasks
Structure of the lecturePresentation hints and tips
FeedbackGroups
Online Material
Aims of the courseTasks
Structure of the lecturePresentation hints and tips
FeedbackGroups
Aims of the Course
The aims of the Case Studies module are:
• to broaden participants’ exposure to practical aspects of statistics;
• to develop in participants a critical awareness of how statistical
ideas and techniques are used in practice;
(See ‘Scientific Thinking’ excerpt on class page)
• to improve the participants’ skill in formulating and delivering a
presentation on a statistical topic; and
• to encourage the development of participants’ group work skills.
Aims of the CourseWhy?
The aims of the Case Studies module are:
• to broaden participants’ exposure to practical aspects of statistics;
• to develop in participants a critical awareness of how statistical
ideas and techniques are used in practice;
(See ‘Scientific Thinking’ excerpt on class page)
• to improve the participants’ skill in formulating and delivering a
presentation on a statistical topic; and
• to encourage the development of participants’ group work skills.
Aims of the CourseWhy?
The aims of the Case Studies module are:
• SO THAT YOU BECOME WELL-ROUNDED STATISTICIANS
• to develop in participants a critical awareness of how statistical
ideas and techniques are used in practice;
(See ‘Scientific Thinking’ excerpt on class page)
• to improve the participants’ skill in formulating and delivering a
presentation on a statistical topic; and
• to encourage the development of participants’ group work skills.
Aims of the CourseWhy?
The aims of the Case Studies module are:
• SO THAT YOU BECOME WELL-ROUNDED STATISTICIANS
• to develop in participants a critical awareness of how statistical
ideas and techniques are used in practice;
(See ‘Scientific Thinking’ excerpt on class page)
• to improve the participants’ skill in formulating and delivering a
presentation on a statistical topic; and
• to encourage the development of participants’ group work skills.
Aims of the CourseWhy?
The aims of the Case Studies module are:
• SO THAT YOU BECOME WELL-ROUNDED STATISTICIANS
• DEVELOPMENT OF CRITICAL THINKING AND PRACTICALITIES OF
STATISTICS IN THE REAL WORLD
• to improve the participants’ skill in formulating and delivering a
presentation on a statistical topic; and
• to encourage the development of participants’ group work skills.
Aims of the CourseWhy?
The aims of the Case Studies module are:
• SO THAT YOU BECOME WELL-ROUNDED STATISTICIANS
• DEVELOPMENT OF CRITICAL THINKING AND PRACTICALITIES OF
STATISTICS IN THE REAL WORLD
• to improve the participants’ skill in formulating and delivering a
presentation on a statistical topic; and
• to encourage the development of participants’ group work skills.
Aims of the CourseWhy?
The aims of the Case Studies module are:
• SO THAT YOU BECOME WELL-ROUNDED STATISTICIANS
• DEVELOPMENT OF CRITICAL THINKING AND PRACTICALITIES OF
STATISTICS IN THE REAL WORLD
• DIRECTLY TRANSFERABLE SKILLS
• to encourage the development of participants’ group work skills.
Aims of the CourseWhy?
The aims of the Case Studies module are:
• SO THAT YOU BECOME WELL-ROUNDED STATISTICIANS
• DEVELOPMENT OF CRITICAL THINKING AND PRACTICALITIES OF
STATISTICS IN THE REAL WORLD
• DIRECTLY TRANSFERABLE SKILLS
• to encourage the development of participants’ group work skills.
Aims of the CourseWhy?
The aims of the Case Studies module are:
• SO THAT YOU BECOME WELL-ROUNDED STATISTICIANS
• DEVELOPMENT OF CRITICAL THINKING AND PRACTICALITIES OF
STATISTICS IN THE REAL WORLD
• DIRECTLY TRANSFERABLE SKILLS
• DIRECTLY TRANSFERABLE SKILLS
AND
PRACTICE FOR ASSESSED GROUP PRACTICAL
Online Material
Aims of the courseTasks
Structure of the lecturePresentation hints and tips
FeedbackGroups
TasksEach student will:
• study 1 case, for main presentation, in randomly allocated groups of 4-5;
• be assigned to speak for part of one presentation (at least);
• study 1 case, for debate-style presentation, in randomly allocated groups of 2-3;
• study cases for question rounds, in randomly allocated groups of 1-2;
• produce a short Personal Reflection for each group work task.
Please note that finding papers in the Oxford library system is part of the task.
Online Material
Aims of the courseTasks
Structure of the lecturePresentation hints and tips
FeedbackGroups
Structure of Lectures
The lectures for this course will be as follows:
– Seminar-style presentation of main case study– followed by ‘quick-fire’ questions– followed by active discussion from the audience
– Debate-style presentation of second case study– followed by active discussion from the audience
Structure of Lectures
The lectures for this course will be timed as follows:
– Seminar-style presentation of main case study 15 minutes– followed by ‘quick-fire’ questions 10 minutes
– Debate-style presentation of second case study 5 minutes each– followed by active discussion from the audience 5 minutes
Online Material
Aims of the courseTasks
Structure of the lecturePresentation hints and tips
FeedbackGroups
Seminar-Style Presentations
• Every member of the group should contribute significantly (but not necessarily equally) to the presentation.
• You are not expected to analyse the data yourselves, and
please do not discuss the theory - this should be a study of examples.
Seminar-Style PresentationsA good presentation will:• clearly and efficiently communicate the context, aims, methods
and findings of the reported analysis;
• deliver a clear, fair and accurate critique of the reported analysis;
• suggest alternative analyses or ideas for improvement if appropriate; and
• deal appropriately and constructively with questions and feedback from the audience.
See ‘Presentation hints’ on the class page
Seminar-Style Presentations• Remember that the audience will not have seen the report.
• Common mistake: Groups do not clearly introduce the problem or describe the context of the analysis. This makes the rest of the presentation almost impossible to follow.
• Technology:You can make use of the computer projector but do prepare in advance, e.g. have the file on your desktop, and log on to the computer before the talk (it takes much longer to log-in the first time you use it!).
Debate-Style Presentations
• Each debate group will present the positive OR negative aspects (as assigned) of the case study
• These are 5 minute short key point presentations
• Every member of the group should contribute significantly (but not necessarily equally) to the presentation.
Quick-Fire Question Rounds
• Lead by the ‘quick-fire’ question group after the presentation.
• ‘Quick-fire’ question group members will– be familiar with the case study– focus on positive OR negative aspects of the study (as assigned) – have a few short (but interesting) questions for the main
presentation group.
• The idea is not to try to catch the presentation group out but to encourage active discussion of the case study.
• ‘Quick-fire’ question rounds will develop into the general questions and discussion with the rest of the audience.
Online Material
Aims of the courseTasks
Structure of the lecturePresentation hints and tips
FeedbackGroups
Feedback
• At the end of the lecture (as you leave)• Post-it anonymous feedback
All students will have an opportunity to receive individual feedback on their presentation.
General feedback also given to each group after the session (e.g. statistical key points and feedback on presentation/team work)
Feedback
Feedback is valuable – It helps you to assess your performance, and to improve.
However, please keep the following in mind:• Feedback should be positive or constructive, but never
negative.• Feedback should not be personal - you are communicating
your perception of the presentation, not making a value judgement about an individual.
• Please consult feedback notes online before the first session
Online Material
Aims of the courseTasks
Structure of the lecturePresentation hints and tips
FeedbackGroups
GroupsGroupwork • Each individual will bring a different set of skills and background
knowledge to the group.
• You will therefore get the most out of the exercise if you work together to prepare the presentation.
• Make sure every meeting has a focus, and that each individual is given the chance to contribute their ideas and skills.
• You may find it useful at first to assign someone the role of chairman, in order to make sure that the discussion stays on track.
Remember this is all practice for the Assessed Group Practical
GroupsAllocation
Students will be assigned to randomly allocated groups for
• Main case study Seminar-Style presentation – Groups of 4-5• Second case study Debate-Style presentation – Groups of 3-4• Quick-fire Question Groups for Main case study – Groups of 2-3
• The references for case studies to be discussed will be available one week before each session
Groups
Tasks
Each main presentation group will:• formulate and deliver a 15 min presentation on a particular
case;• be prepared for ‘quick-fire’ questions and general questions
from the audience; and• produce a team plan – to be submitted no later than 24 hours
before presentation.
Groups
Tasks
Each debate presentation group will:• formulate and deliver a 5 min presentation on a particular case;• be prepared to defend their comments; and• produce a team plan – to be submitted no later than 24 hours
before presentation.
Groups
Tasks
Each ‘quick-fire’ question group will:• briefly review the case to be presented; and• prepare 1-2 interesting questions for discussion with the
presentation group.
Online Material
Aims of the courseTasks
Structure of the lecturePresentation hints and tips
FeedbackGroups
Team Plan and Personal Reflection
Team Plan & Personal Reflection
Each presentation group will submit a TEAM PLAN no less than 24 hours before the presentation (i.e. By 11am Thursday)
The TEAM PLAN will outline the individual roles of each student in the groupe.g. presenter, slide writer ...
Team Plan & Personal Reflection
Each student will produce a short Personal Reflection for each group work task in which they are involved
To be submitted by 2pm Monday morning
By Week 8 each student should have three Personal Reflections
A Personal Reflection should be • an individual piece of writing • no more than a single page • a brief description of your own experience of a particular
groupwork task
Linear ModelsM.Sc. in Applied Statistics
Dr. Órlaith BurkeMichaelmas Term 2013
Course Overview
1. Linear Regression2. Multiple Linear Regression3. Prediction and Residual Diagnostics4. Resistant Regression5. Classical Applications to ANOVA
Course Overview
Breakdown:
6 Lectures1 Assignment
1 Class2 Practicals:
1 of which is an Assessed Practical
AutocorrelationM.Sc. in Applied Statistics
Dr. Órlaith BurkeMichaelmas Term 2013
Course Overview
1. Basics and Introduction2. Identification and Estimation3. Non-Stationarity4. Diagnostics and Forecasting5. Decomposition and MCMC Output
Course Overview
Breakdown:
4 Lectures1 Assignment
1 Class2 Practicals:
1 of which is an Assessed Practical
Course Overview
Lecture Slides Notes
Reading Lecture time will be aimed at discussion of topics and examples
Reading will be required!