A pinboard by
George Ng

Ph.D in Biotechnology who has joined a eCommerce startup in Hong Kong


Polls struggle to match election results, is the error an inherent bias or are polls a 'black art'?

Led Astray On the evening of Nov. 8, 2016 voters were aghast with disbelief, as the Clinton Trump election results rolled in. Nate Silver's FiveThirtyEight's projections - who have correctly forecast the winner of nearly every state, since 2008 - 2012 handed a 72% probability for a Clinton victory. The New York Times model gave Clinton a 85% chance, whilst the Princeton Election Consortium placed Clinton to win at 99%. How did the polls struggle to match election results? As the beautifully crafted poll simulation pointed out reporting on polling results need to account for a 'margin of error' and explain any inherent bias that skews the data.

Margin Of Error Nate Cohn does a deep dive into statistical weights or bias of polls and how one man in Illinois is distorting National Polling Averages. The unnamed person is one of 3000 panelist of the U.S.C. Dornsife/LA Times Daybreak poll, who is determined to vote Trump. According to the article, in some polls, he's weighted as much as 30 times above the average respondent, or 300 times more than the least weighted respondent.

What Happened? Polls aggregate information about voter preferences, studies have shown that when the electorate is small and voting costs are negligible, an equilibrium exists - voters report their true political alliances. When the electorate is large or voting costs are significant, poll respondents possess incentives to influence voting behaviour of others by misreporting their true preferences.


Biased polls and the psychology of voter indecisiveness

Abstract: Accounting for undecided and uncertain voters is a challenging issue for predicting election results from public opinion polls. Undecided voters typify the uncertainty of swing voters in polls but are often ignored or allocated to each candidate in a simplistic manner. Historically this has been adequate because first, the undecided tend to settle on a candidate as the election day draws closer, and second, they are comparatively small enough to assume that the undecided voters do not affect the relative proportions of the decided voters. These assumptions are used by poll authors and meta-poll analysts, but in the presence of high numbers of undecided voters these static rules may bias election predictions. In this paper, we examine the effect of undecided voters in the 2016 US presidential election. This election was unique in that a) there was a relatively high number of undecided voters and b) the major party candidates had high unfavorability ratings. We draw on psychological theories of decision making such as decision field theory and prospect theory to explain the link between candidate unfavorability and voter indecisiveness, and to describe how these factors likely contributed to a systematic bias in polling. We then show that the allocation of undecided voters in the 2016 election biased polls and meta-polls in a manner consistent with these theories. These findings imply that, given the increasing number of undecided voters in recent elections, it will be important to take into account the underlying psychology of voting when making predictions about elections.

Pub.: 28 Mar '17, Pinned: 19 Apr '17

How the polls can be both spot on and dead wrong: using choice blindness to shift political attitudes and voter intentions.

Abstract: Political candidates often believe they must focus their campaign efforts on a small number of swing voters open for ideological change. Based on the wisdom of opinion polls, this might seem like a good idea. But do most voters really hold their political attitudes so firmly that they are unreceptive to persuasion? We tested this premise during the most recent general election in Sweden, in which a left- and a right-wing coalition were locked in a close race. We asked our participants to state their voter intention, and presented them with a political survey of wedge issues between the two coalitions. Using a sleight-of-hand we then altered their replies to place them in the opposite political camp, and invited them to reason about their attitudes on the manipulated issues. Finally, we summarized their survey score, and asked for their voter intention again. The results showed that no more than 22% of the manipulated replies were detected, and that a full 92% of the participants accepted and endorsed our altered political survey score. Furthermore, the final voter intention question indicated that as many as 48% (±9.2%) were willing to consider a left-right coalition shift. This can be contrasted with the established polls tracking the Swedish election, which registered maximally 10% voters open for a swing. Our results indicate that political attitudes and partisan divisions can be far more flexible than what is assumed by the polls, and that people can reason about the factual issues of the campaign with considerable openness to change.

Pub.: 18 Apr '13, Pinned: 25 Apr '17