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1 What makes a good presentation? 2. The slides 3. The talk 4. Miscellaneous 1. Structure

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2 present as few equations as possible 1. Presentation paper motivation is most important!!! (see Economic History presentations) emphasize the economic intuition ?

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3 Put yourself into the shoes of someone who 1. Presentation paper 2. Rule of thumb: doesn’t know much about your topic, literature, details Best example: Recall how you felt during the most recent seminars implement what you liked avoid what put you to sleep 1. Structure

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4 (Brief outline of your talk) (Motivation of your topic) (Describe the essential parts of your economic/econometric model) 1. “What is the point of being here?” 3. Outline of a good presentation: (Very briefly relate your work to the existing literature) (Present, explain, and discuss your results) 3. “What is new?” 4. “What do I need to know to understand your results?” 2. “When can I ask what question?” 1. Presentation paper 2. Rule of thumb 5. “What should I learn from your talk?” 1. Structure

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5 2. The Slides 12 point font won’t do! (1) (2) (3) (4) (5)

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6 2. The Slides 12 point font won’t do! 20 point font is the absolute minimum 28 point font is even better Don’t do fancy things with 10 – 12 slides maximum for a 40 minute presentation Don’t overload your slides Don’t have too many slides The 4 most important rules

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7 predicted shares observed shares If you need to show equations: make them simple! Rankings Elections mean loglikelihood ratio Number of voters Kernel of the multinomial distribution 2. The Slides

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8 Table 3. Assessment of six models of voter behavior Analysis of observed election data Analysis of simulated data ( “ impartial anonymous culture assumption ” ) Degrees of freedom Mean LLR Mean WSSR AICBICMean LLR Mean WSSR (1)(2)(3)(4)(5)(6)(7) Equally likely rankings 0-196.80 (4.26) 207.28 (4.42) 359,357 -535.12 (0.31) 581.00 (0.41) Unequally likely rankings 5-31.15 (0.97) 32.45 (0.88) 56,89056,922-161.00 (0.15) 160.22 (0.17) Borda model913-116.79 (2.72) 121.00 (2.78) 215,085220,951-367.14 (0.23) 363.84 (0.24) Condorcet model913-84.99 (2.00) 88.36 (2.25) 157,018162,885-297.27 (0.20) 283.20 (0.20) Spatial model3,652-0.87 (0.05) 0.97 (0.06) 8,89332,360-73.15 (0.11) 65.13 (0.09) Notes: 1. Standard errors of estimate of the estimated means are shown in parentheses. 2. To facilitate comparisons, we have multiplied the statistics reported in Columns (3) and (7) by 1,000,000. 3. We calculated the AIC and BIC in Columns (4) and (5) using the LLRs in Column (2), which share the same denominator. Thus the two measures of fit differ from the conventional measures by an additive constant. 4. To determine the BIC in Column (5), note that there are 5 913 – 1 = 4,564 degrees of freedom in the data. Don’t reproduce tables from your paper

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9 Analysis of observed election data Analysis of simulated data ( “ impartial anonymous culture ” ) mean LLR Equally likely rankings (IC) -196.80 (4.26) -535.12 (0.31) Unequally likely rankings -31.15 (0.97) -161.00 (0.15) Borda model-116.79 (2.72) -367.14 (0.23) Condorcet model-84.99 (2.00) -297.27 (0.20) Spatial model-0.87 (0.05) -73.15 (0.11) Note: Standard errors of estimate of the estimated means in parentheses. Assessment of six models of voter behavior

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10 Analysis of observed election data mean LLR Equally likely rankings (IC) -196.80 (4.26) Unequally likely rankings -31.15 (0.97) Borda model-116.79 (2.72) Condorcet model-84.99 (2.00) Spatial model-0.87 (0.05) Note: Standard errors of estimate of the estimated means in parentheses. Assessment of six models of voter behavior

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11 Analysis of observed election data Analysis of simulated data ( “ impartial anonymous culture ” ) mean LLR Equally likely rankings (IC) -196.80 (4.26) -535.12 (0.31) Unequally likely rankings -31.15 (0.97) -161.00 (0.15) Borda model-116.79 (2.72) -367.14 (0.23) Condorcet model-84.99 (2.00) -297.27 (0.20) Spatial model-0.87 (0.05) -73.15 (0.11) Note: Standard errors of estimate of the estimated means in parentheses. Assessment of six models of voter behavior

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12 Don’t show anything on a slide that you do not plan to discuss in your presentation Don’t write out text in long paragraphs with detailed definitions that your audience cannot possibly digest at a single glance because your explanation is too longwinded and tedious. use short bullet points add verbal explanations use graphics when possible 2. The Slides

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13 3. The talk Don’t read your slides!

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14 3. The talk the slides are for your audience, not for you write everything you plan to say on paper … but don’t read your presentation from that paper practice your talk, with all your slides, - in front of a mirror - with your friends slides should have only short bullet points

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15 3. The talk only make things appear and disappear on your slides if you know your presentation cold otherwise: show the entire slide don’t be afraid of questions If you cannot answer the question, say “That is a good question. I haven’t thought about it yet.” Write the question down and work on it when you are back in your office

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16 3. The talk if you describe an equation, use the variable names and not their symbols This is not “beta” but “the marginal propensity to consume”

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17 look at your audience, not at your shoes speak loudly enough smile 3. The talk your audience is your friend, not your enemy if you get nervous, imagine that everyone in the audience is naked

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18 4. Miscellaneous arrive at least 15 minutes early to set up your equipment have a backup plan in case something does not work email your presentation to yourself (in case the flash drive fails) bring a printout of your presentation (to make transparencies if the computer fails) be prepared to talk even without your slides (in case the projector fails)

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19 Thank your audience for coming! It is bad if your presentation ends with “that’s it!”

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