Tips for Oral Presentations

Why Give Oral Presentations?

Effective communication is essential to show your workto the scientific community

Journal articles are one way to do this.

Presentations at seminars and conferences are anotherway.

Why Give Oral Presentations?

Presentations at conferences are either posters ororal presentations.

At the big statistical conferences (JSM and ENAR), about 80-90% of the presentations are talks.

General Format for Talks

Session 273: Missing Data and Dropout in the Analysis ofLongitudinal data--Contributed

2:05 pm Do Mixed Model and Multiple Imputations Work Together for Longitudinal Data Analysis with Missing Values?

2:20 pm A Two-part Model for Longitudinal Data with Missing Values

2:35 pm Analysis of Longitudinal Data with Nonmonotone, Nonignorable Missing Data

...3:20 pm Mixed Effects Models for Truncated Longitudinal

Outcome and Nonignorable Missing Data

What Do You Need for a Good Talk?

Good slidesContentStyle

Good delivery

Good material = Good talk

Not necessarily true!

Good Slides: Content

Always start with a title slide

Presentation title

Authors

Support

Contact info

Good Slides: Content

What is the problem and why is it a problem? What has been done about it before? What is the presenter doing (or has done) about it? What additional value does the presenter’s approach provide?Where do we go from here?

What the listener wants to know:

Organize your presentation to address those 5 questions.

At statistics conferences... aim your presentation to an audience of colleagues whoknow the concepts but not the details

Good Slides: Content

Don’t present theoretical statistical development to anaudience of MPH epidemiology students.

Know who your audience is and put your material in a context suitable to the audience.

General Format for Talks

Session 273: Missing Data and Dropout in the Analysis ofLongitudinal data--Contributed

2:05 pm Do Mixed Model and Multiple Imputations Work Together for Longitudinal Data Analysis with Missing Values?

2:20 pm A Two-part Model for Longitudinal Data with Missing Values

2:35 pm Analysis of Longitudinal Data with Nonmonotone, Nonignorable Missing Data

...3:20 pm Mixed Effects Models for Truncated Longitudinal

Outcome and Nonignorable Missing Data

Remember the goal:

Your objective is to communicate an appreciation of the importance of your work, not just to lay the results out.

You always can and should give references and a way to contact you so those interested in the theoretical details can follow up with the literature or with you.

Good Slides: Content

Providing handouts is a good idea

25 mins. worth of talk dragged out for 45 minutes

Good Slides: Content

Budget your time carefully

25 mins. worth of talk crammed into 15 minutes

Allow enough time to describe the problem you address clearly enough for the audience to appreciate the value of your contribution.

This usually will take more than 30 seconds.

Good Slides: Content

Leave enough time to present your own contribution clearly. This almost never will require all of the allotted time.

1. Use simple fonts like Arial or Tahoma, not ornate fonts like Times New Roman or Corsiva.

Good Slides: Style

1. Use simple fonts like Arial or Tahoma, not ornate fonts likeTimes New Roman or Corsiva.

2. Use 24 point type or bigger.

Good Slides: Style

2. Use 24 point type or bigger.

Good Slides: Style

1. Use 24 point type or bigger.

2. Use simple fonts like Arial or Tahoma, not ornate fonts likeTimes New Roman or Corsiva.

3. Try to limit the material to 8 lines per slide. Summarize the main points – don’t include every detail of what you plan to say.

1. Use 24 point type or bigger.

2. Use simple fonts like Arial or Tahoma, not ornate fonts likeTimes New Roman or Corsiva.

3. Try to limit the material to 8 lines per slide. Summarize the main points – don’t include every detail of what you plan to say.

3. Try to limit the material to 8 lines per slide.

• Summarize the main points

• Don’t include every detail of what you plan to say

• Bullets can be effective

Good Slides: Style

Good Slides: StyleSample characteristics Blood Pressure Status  

Normotensive Pre-ypertensive Hypertensive p

SBP 103.4 + 0.16 109.1 + 0.27 110.4 + 0.41 0.0001

DBP 63.9 + 0.13 66.2 + 0.23 68.8 + 0.35 0.0001

Pulse Pressure 39.7 + 0.15 42.6 + 0.26 41.5 + 0.39 0.0001

MAP 76.9 + 0.13 80.6 + 0.22 82.7 + 0.33 0.0001

BMI 19.6 + 0.9 20.5 + 0.15 21.5 + 0.21 0.0001

SS skinfold 10.9 + 0.17 12.7 + 0.29 14.2 + 0.45 0.0001

TR skinfold 14.8 + 0.13 16.3 + 0.23 17.8 + 0.34 0.0001

Triglycerides 59.3 + 1.01 62.0 + 1,01 65.1 + 1.02 0.0001

Insulin 9.2 + 1.01 9.9 + 1.02 11.6 + 1.04 0.0001

Insulin Resistance 1.86 + 0.0001 2.16 + 0.0004 2.77 + 0.0011 0.0001

Glucose 81.3 + 0.24 84.3 + 0.41 85.9 + 0.62 0.0001

         

HDL 59.2 + 0.35 58.5 + 0.59 58.4 + 0.88 ns

LDL 90.6 + 0.54 91.5 + 0.91 93.3 + 1.4 ns

Total Cholesterol 158.3 + 0.58 158.8 + 0.98 161.1 + 1.46 ns

4. Limit the tables to 4 rows/columns for readability.

Sacrifice content for legibility – unreadable content is worse than useless.

Good Slides: Style

5. For slides, use light letters (yellow or white) on a dark background (e.g., dark blue). Limit the number of colors in your text.

5. For slides, use light letters (yellow or white) on a dark background (e.g., dark blue). Limit the number of colors in your text.

Good Slides: Style

6. Don’t put a lot of curves on a graphical display – busy graphical displays are hard to read. Label your graphs clearly with BIG, READABLE TYPE Legends are absolutely necessary

Good Slides: Style

5-8 9-11 12-19 20-24 25-27 > 27

0

20

40

60

80

100

120

140

7. Use equations sparingly if at all; avoid derivations.

Good Slides: Style

)|(LlogE

)]('h[)|)̂(h(Var

2

2

2

X

p1

pln)(hWhen

)|p(LlogE

p̂-1p̂

lnp

pp̂-1

p̂lnVar

2

2

p

2

X

we obtain

)p1(pn

)p1(p

122

n)p1(p

1

8. Keep it simple.

Good Slides: Style

etc does not mean that you should.

The fact that you can include all kinds of cute animation

pictures

9. Always purview your slides.

Good Slides: Style

There’s no excuse for a misspelled word on a slide.

______

Careful about translating between different applications

Fonts available on the computer where you made your slidemay not be available on the computer that produces yourslide.

Good Delivery: Timing

Few things irritate an audience more than a 30 minute talk delivered in 15 minutes.

Present only as much material as can reasonably fit into the time period allotted.

1 slide per minute

Talk at a pace that everybody in the audience can understand. Speak slowly, clearly, and loudly, especially if your English is heavily accented.

Balance the amount of material you present with a reasonable pace of presentation.

If you feel rushed when you practice, then you have toomuch material.

PRACTICE, PRACTICE, PRACTICE.

Good Delivery: Timing

PRACTICE, PRACTICE, PRACTICE.

Alone: in the mirror

Good Delivery: Timing

Make sure you do not block the screen.

Don’t bounce, pace, jangle your keys, or twist your rings.

Ask a colleague to judge your presentation, delivery, clarity of language, and use of time.

Good Delivery: Presentation

The audience wants to hear what you have to say

Autopilot effect

Don’t apologize

The audience knows how to read

Good Delivery: Presentation

Don’t apologize for incomplete results. Researchers understand that all research continues. Just present the results and let the audience judge.

Beware the laser pointer

but don’t point at the computer screen

Take all questions seriously, no matter how stupid you thinka particular question is.

It’s okay if your answer is “I don’t know”.

Be diplomatic.

Invite persistent questioners to discuss the topic with you after the session.

Good Delivery: Audience Manners

Duplicate questions still deserve answers

Presentation Tips Resources

Many of these tips are culled from the ENAR guidelines to effective presentations.

www.enar.org

Also see

Freeman, DH, Gonzalez, ME, Hoaglin, DC, &Kilss, BA. (1983).Presenting statistical papers. American Statistician, 37:106-110

Becker, RA & Keller-McNulty, S. (1996). Presentation myths.American Statistician, 50:112-115

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