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Case Studies M.Sc. in Applied Statistics Dr. Órlaith Burke Michaelmas Term 2013

Case Studies M.Sc. in Applied Statistics

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Case Studies M.Sc. in Applied Statistics. Dr. Órlaith Burke Michaelmas Term 2013. Linear Models M.Sc. in Applied Statistics. Dr. Órlaith Burke Michaelmas Term 2013. Autocorrelation M.Sc. in Applied Statistics. Dr. Órlaith Burke Michaelmas Term 2013. - PowerPoint PPT Presentation

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Page 1: Case Studies M.Sc. in Applied Statistics

Case StudiesM.Sc. in Applied Statistics

Dr. Órlaith BurkeMichaelmas Term 2013

Page 2: Case Studies M.Sc. in Applied Statistics

Linear ModelsM.Sc. in Applied Statistics

Dr. Órlaith BurkeMichaelmas Term 2013

Page 3: Case Studies M.Sc. in Applied Statistics

AutocorrelationM.Sc. in Applied Statistics

Dr. Órlaith BurkeMichaelmas Term 2013

Page 4: Case Studies M.Sc. in Applied Statistics

Statistical MethodsM.Sc. in Applied Statistics

Page 5: Case Studies M.Sc. in Applied Statistics

Statistical MethodsM.Sc. in Applied Statistics

Hard work

Page 6: Case Studies M.Sc. in Applied Statistics

Statistical MethodsM.Sc. in Applied Statistics

Hard work = Stay engaged

Page 7: Case Studies M.Sc. in Applied Statistics

Statistical MethodsM.Sc. in Applied Statistics

Hard work = Stay engagedResponsibility

Page 8: Case Studies M.Sc. in Applied Statistics

Statistical MethodsM.Sc. in Applied Statistics

Hard work = Stay engagedResponsibility = Ownership

Page 9: Case Studies M.Sc. in Applied Statistics

Statistical MethodsM.Sc. in Applied Statistics

Hard work = Stay engagedResponsibility = Ownership

Read

Page 10: Case Studies M.Sc. in Applied Statistics

Statistical MethodsM.Sc. in Applied Statistics

Hard work = Stay engagedResponsibility = Ownership

Read = Read

Page 11: Case Studies M.Sc. in Applied Statistics

Case Studies

‘Other’ skillsTransferable skills

Page 12: Case Studies M.Sc. in Applied Statistics

Case Studies

Presentation skills

Page 13: Case Studies M.Sc. in Applied Statistics

Case Studies

Presentation skillsGroupwork

Page 14: Case Studies M.Sc. in Applied Statistics

Case Studies

Presentation skillsGroupwork

Critical Thinking

Page 15: Case Studies M.Sc. in Applied Statistics

Case Studies

Presentation skillsGroupwork

Critical ThinkingSynthesis of Ideas

Page 16: Case Studies M.Sc. in Applied Statistics
Page 17: Case Studies M.Sc. in Applied Statistics

Case Studieso Logisticso Aims of the courseo Taskso Structure of the Lectureso Presentation typeso Feedback o Personal Reflectiono Groups: Allocation, tasks and group work

Page 18: Case Studies M.Sc. in Applied Statistics

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

Page 19: Case Studies M.Sc. in Applied Statistics

Online Material

Aims of the courseTasks

Structure of the lecturePresentation hints and tips

FeedbackGroups

Page 20: Case Studies M.Sc. in Applied Statistics

Online Material

Aims of the courseTasks

Structure of the lecturePresentation hints and tips

FeedbackGroups

Page 21: Case Studies M.Sc. in Applied Statistics

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.

Page 22: Case Studies M.Sc. in Applied Statistics

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.

Page 23: Case Studies M.Sc. in Applied Statistics

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.

Page 24: Case Studies M.Sc. in Applied Statistics

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.

Page 25: Case Studies M.Sc. in Applied Statistics

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.

Page 26: Case Studies M.Sc. in Applied Statistics

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.

Page 27: Case Studies M.Sc. in Applied Statistics

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.

Page 28: Case Studies M.Sc. in Applied Statistics

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.

Page 29: Case Studies M.Sc. in Applied Statistics

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

Page 30: Case Studies M.Sc. in Applied Statistics

Online Material

Aims of the courseTasks

Structure of the lecturePresentation hints and tips

FeedbackGroups

Page 31: Case Studies M.Sc. in Applied Statistics

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.

Page 32: Case Studies M.Sc. in Applied Statistics

Online Material

Aims of the courseTasks

Structure of the lecturePresentation hints and tips

FeedbackGroups

Page 33: Case Studies M.Sc. in Applied Statistics

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

Page 34: Case Studies M.Sc. in Applied Statistics

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

Page 35: Case Studies M.Sc. in Applied Statistics

Online Material

Aims of the courseTasks

Structure of the lecturePresentation hints and tips

FeedbackGroups

Page 36: Case Studies M.Sc. in Applied Statistics

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.

Page 37: Case Studies M.Sc. in Applied Statistics

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

Page 38: Case Studies M.Sc. in Applied Statistics

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!).

Page 39: Case Studies M.Sc. in Applied Statistics

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.

Page 40: Case Studies M.Sc. in Applied Statistics

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.

Page 41: Case Studies M.Sc. in Applied Statistics

Online Material

Aims of the courseTasks

Structure of the lecturePresentation hints and tips

FeedbackGroups

Page 42: Case Studies M.Sc. in Applied Statistics

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)

Page 43: Case Studies M.Sc. in Applied Statistics

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

Page 44: Case Studies M.Sc. in Applied Statistics

Online Material

Aims of the courseTasks

Structure of the lecturePresentation hints and tips

FeedbackGroups

Page 45: Case Studies M.Sc. in Applied Statistics

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

Page 46: Case Studies M.Sc. in Applied Statistics

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

Page 47: Case Studies M.Sc. in Applied Statistics

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. 

Page 48: Case Studies M.Sc. in Applied Statistics

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. 

Page 49: Case Studies M.Sc. in Applied Statistics

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.

Page 50: Case Studies M.Sc. in Applied Statistics

Online Material

Aims of the courseTasks

Structure of the lecturePresentation hints and tips

FeedbackGroups

Team Plan and Personal Reflection

Page 51: Case Studies M.Sc. in Applied Statistics

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 ...

Page 52: Case Studies M.Sc. in Applied Statistics

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

Page 53: Case Studies M.Sc. in Applied Statistics

Linear ModelsM.Sc. in Applied Statistics

Dr. Órlaith BurkeMichaelmas Term 2013

Page 54: Case Studies M.Sc. in Applied Statistics

Course Overview

1. Linear Regression2. Multiple Linear Regression3. Prediction and Residual Diagnostics4. Resistant Regression5. Classical Applications to ANOVA

Page 55: Case Studies M.Sc. in Applied Statistics

Course Overview

Breakdown:

6 Lectures1 Assignment

1 Class2 Practicals:

1 of which is an Assessed Practical

Page 56: Case Studies M.Sc. in Applied Statistics

AutocorrelationM.Sc. in Applied Statistics

Dr. Órlaith BurkeMichaelmas Term 2013

Page 57: Case Studies M.Sc. in Applied Statistics

Course Overview

1. Basics and Introduction2. Identification and Estimation3. Non-Stationarity4. Diagnostics and Forecasting5. Decomposition and MCMC Output

Page 58: Case Studies M.Sc. in Applied Statistics

Course Overview

Breakdown:

4 Lectures1 Assignment

1 Class2 Practicals:

1 of which is an Assessed Practical

Page 59: Case Studies M.Sc. in Applied Statistics

Course Overview

Lecture Slides Notes

Reading Lecture time will be aimed at discussion of topics and examples

Reading will be required!