Tech Could Learn from the Election: Big Data Rules

XKCD xartoon

I have wanted to write about the growing importance of big data and analytics for a while, but this is a tech site and I did not want to get it embroiled in the political tempests. But now that the votes have been counted, we have a stunning demonstration of the power of data, as suggested by the XKCD cartoon above.

In the closing days of the campaign, New York Times blogger Nate Silver emerged as a lightening rod. He drew fire from both Republicans and traditional pundits of all stripes for his insistence that despite the closeness of the polls, both nationally and in key states, that President Obama was an overwhelming favorite to win re-election by a narrow margin in the popular vote and a much larger one in the electoral college. He was, of course, dead on.

People who are now hailing Silver as the greatest political pundit ever are completely missing the point, because Silver’s approach was about as far as you can get from the seat-of-the-pants, anecdotal methods of pundits. He went with the data.

Silver’s best friend was something known to mathematicians and statisticians as the law of large numbers. What this theorem, first developed in the 18th century, says is that as you take many samples some some phenomenon, say the percentage of voters supporting Obama in Ohio, the results of these tests will cluster around the true value. (The law’s cousin, the central limit theorem, allows much great specificity about the nature of that clustering, but also is subject to much more stringent restrictions.)

Pundits kept focusing on individual polls and the fact that the difference fell within the margin of error.* Silver understood that as you used more and more polls, the probable error of the aggregated result shrank. In other words (and very roughly) if 10 polls each show Candidate A with a one point lead, you can be reasonably confident that A is in the lead even though the error of each poll is plus or minus three points.

Silver also used a tool that gave him a way to quantify predictions. Now a model necessarily involves making a lot of assumptions. For example, Silver’s novel (which he has been reasonably transparent about, though he has never released its detailed specification) assigned a fairly heavy weight to key economic indicators early in the campaign, but reduced the weight as time went on based on the assumption that new data have less effect as election day nears. It also involves weighting the influence of polls based on their track record and “house effect” (a tendency to favor on party or candidate relative to other polls. He then used to model to run thousands of daily simulations of possible outcomes, a sort of Monte Carlo method. His probability of victory on any given day was simply the percentage of simulations in which a candidate emerged as the winner.

This sort of analysis has only recently become possible. First, we didn’t have the raw data. There were fewer polls, and greater lags between the collection of data and its release. Second, until the recent massive increases in cheap and available computing power, doing thousands of daily runs of a model of any complexity was impossible. A similar phenomenon lies behind the increased accuracy of weather forecasts, including the extremely accurate predictions of the course and effects of Hurricane Sandy. Weather forecasters use supercomputers for their simulations because the models are far more complex, but the techniques and the beenfits are much the same.

Too bad we don’t have more data-driven analysis in tech. Of course, there’s the big problem that a lot of the necessary data just isn’t available. Only Apple, Amazon, and Samsung know exactly how many of which products they sell, and they are not inclined to share the information. Still, there are analysts who make the most of the data. Two who come to mind are Horace Dediu of Asymco, who keeps tabs on the handset business, and Mary Meeker of Kleiner Perkins, who provides infrequent but deep data dives. We could badly use more data and less posturing.

*–Poll margin of error is one of the most misunderstood concepts around. First of all, the term should be abandoned. The correct concept is a confidence interval; what you are saying when you claim a margin of error is plus or minus three points is that some percentage of the time (the confidence level, typically 95% in polling) the actual result wii be within three points of the reported value. Pollster should act more like engineers and surround their point values with error bars. Second, the size of the confidence interval is purely a function of the sample size and says nothing whatever about how well a poll is executed. So a poll with poorly put questions and a badly drawn but large sample will have a tighter confidence interval than a much better done poll with a smaller sample.

Published by

Steve Wildstrom

Steve Wildstrom is veteran technology reporter, writer, and analyst based in the Washington, D.C. area. He created and wrote BusinessWeek’s Technology & You column for 15 years. Since leaving BusinessWeek in the fall of 2009, he has written his own blog, Wildstrom on Tech and has contributed to corporate blogs, including those of Cisco and AMD and also consults for major technology companies.

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  91. オンラインカジノとオンラインギャンブルの現代的展開
    オンラインカジノの世界は、技術の進歩と共に急速に進化しています。これらのプラットフォームは、従来の実際のカジノの体験をデジタル空間に移し、プレイヤーに新しい形式の娯楽を提供しています。オンラインカジノは、スロットマシン、ポーカー、ブラックジャック、ルーレットなど、さまざまなゲームを提供しており、実際のカジノの興奮を維持しながら、アクセスの容易さと利便性を提供します。

    一方で、オンラインギャンブルは、より広範な概念であり、スポーツベッティング、宝くじ、バーチャルスポーツ、そしてオンラインカジノゲームまでを含んでいます。インターネットとモバイルテクノロジーの普及により、オンラインギャンブルは世界中で大きな人気を博しています。オンラインプラットフォームは、伝統的な賭博施設に比べて、より多様なゲーム選択、便利なアクセス、そしてしばしば魅力的なボーナスやプロモーションを提供しています。

    安全性と規制
    オンラインカジノとオンラインギャンブルの世界では、安全性と規制が非常に重要です。多くの国々では、オンラインギャンブルを規制する法律があり、安全なプレイ環境を確保するためのライセンスシステムを設けています。これにより、不正行為や詐欺からプレイヤーを守るとともに、責任ある賭博の促進が図られています。

    技術の進歩
    最新のテクノロジーは、オンラインカジノとオンラインギャンブルの体験を一層豊かにしています。例えば、仮想現実(VR)技術の使用は、プレイヤーに没入型のギャンブル体験を提供し、実際のカジノにいるかのような感覚を生み出しています。また、ブロックチェーン技術の導入は、より透明で安全な取引を可能にし、プレイヤーの信頼を高めています。

    未来への展望
    オンラインカジノとオンラインギャンブルは、今後も技術の進歩とともに進化し続けるでしょう。人工知能(AI)の更なる統合、モバイル技術の発展、さらには新しいゲームの創造により、この分野は引き続き成長し、世界中のプレイヤーに新しい娯楽の形を提供し続けることでしょう。

    この記事では、オンラインカジノとオンラインギャンブルの現状、安全性、技術の影響、そして将来の展望に焦点を当てています。この分野は、技術革新によって絶えず変化し続ける魅力的な領域です。

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  94. Sight Care is a daily supplement proven in clinical trials and conclusive science to improve vision by nourishing the body from within. The Sight Care formula claims to reverse issues in eyesight, and every ingredient is completely natural.

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  97. 民調
    民意調查是什麼?民調什麼意思?
    民意調查又稱為輿論調查或民意測驗,簡稱民調。一般而言,民調是一種為了解公眾對某些政治、社會問題與政策的意見和態度,由專業民調公司或媒體進行的調查方法。

    目的在於通過網路、電話、或書面等媒介,對大量樣本的問卷調查抽樣,利用統計學的抽樣理論來推斷較為客觀,且能較為精確地推論社會輿論或民意動向的一種方法。
    以下是民意調查的一些基本特點和重要性:

    抽樣:由於不可能向每一個人詢問意見,所以調查者會選擇一個代表性的樣本進行調查。這樣本的大小和抽樣方法都會影響調查的準確性和可靠性。
    問卷設計:為了確保獲得可靠的結果,問卷必須經過精心設計,問題要清晰、不帶偏見,且易於理解。
    數據分析:收集到的數據將被分析以得出結論。這可能包括計算百分比、平均值、標準差等,以及更複雜的統計分析。
    多種用途:民意調查可以用於各種目的,包括政策制定、選舉預測、市場研究、社會科學研究等。
    限制:雖然民意調查是一個有價值的工具,但它也有其限制。例如,樣本可能不完全代表目標人群,或者問卷的設計可能導致偏見。
    影響決策:民意調查的結果常常被政府、企業和其他組織用來影響其決策。
    透明度和誠實:為了維護調查的可信度,調查組織應該提供其調查方法、樣本大小、抽樣方法和可能的誤差範圍等詳細資訊。
    民調是怎麼調查的?
    民意調查(輿論調查)的意義是指為瞭解大多數民眾的看法、意見、利益與需求,以科學、系統與公正的資料,蒐集可以代表全部群眾(母體)的部分群眾(抽樣),設計問卷題目後,以人工或電腦詢問部分民眾對特定議題的看法與評價,利用抽樣出來部分民眾的意見與看法,來推論目前全部民眾的意見與看法,藉以衡量社會與政治的狀態。

    以下是進行民調調查的基本步驟:

    定義目標和目的:首先,調查者需要明確調查的目的。是要了解公眾對某個政策的看法?還是要評估某個政治候選人的支持率?
    設計問卷:根據調查目的,研究者會設計一份問卷。問卷應該包含清晰、不帶偏見的問題,並避免導向性的語言。
    選擇樣本:因為通常不可能調查所有人,所以會選擇一部分人作為代表。這部分人被稱為“樣本”。最理想的情況是使用隨機抽樣,以確保每個人都有被選中的機會。
    收集數據:有多種方法可以收集數據,如面對面訪問、電話訪問、郵件調查或在線調查。
    數據分析:一旦數據被收集,研究者會使用統計工具和技術進行分析,得出結論或洞見。
    報告結果:分析完數據後,研究者會編寫報告或發布結果。報告通常會提供調查方法、樣本大小、誤差範圍和主要發現。
    解釋誤差範圍:多數民調報告都會提供誤差範圍,例如“±3%”。這表示實際的結果有可能在報告結果的3%範圍內上下浮動。
    民調調查的質量和可信度很大程度上取決於其設計和實施的方法。若是由專業和無偏見的組織進行,且使用科學的方法,那麼民調結果往往較為可靠。但即使是最高質量的民調也會有一定的誤差,因此解讀時應保持批判性思考。

    為什麼要做民調?
    民調提供了一種系統性的方式來了解大眾的意見、態度和信念。進行民調的原因多種多樣,以下是一些主要的動機:

    政策制定和評估:政府和政策制定者進行民調,以了解公眾對某一議題或政策的看法。這有助於制定或調整政策,以反映大眾的需求和意見。
    選舉和政治活動:政黨和候選人通常使用民調來評估自己在選舉中的地位,了解哪些議題對選民最重要,以及如何調整策略以吸引更多支持。
    市場研究:企業和組織進行民調以了解消費者對產品、服務或品牌的態度,從而制定或調整市場策略。
    社會科學研究:學者和研究者使用民調來了解人們的社會、文化和心理特征,以及其與行為的關係。
    公眾與媒體的期望:民調提供了一種方式,使公眾、政府和企業得以了解社會的整體趨勢和態度。媒體也經常報導民調結果,提供公眾對當前議題的見解。
    提供反饋和評估:無論是企業還是政府,都可以透過民調了解其表現、服務或政策的效果,並根據反饋進行改進。
    預測和趨勢分析:民調可以幫助預測某些趨勢或行為的未來發展,如選舉結果、市場需求等。
    教育和提高公眾意識:通過進行和公布民調,可以促使公眾對某一議題或問題有更深入的了解和討論。

    民調可信嗎?
    民意調查的結果數據隨處可見,尤其是政治性民調結果幾乎可說是天天在新聞上放送,對總統的滿意度下降了多少百分比,然而大家又信多少?

    在景美市場的訪問中,我們了解到民眾對民調有一些普遍的觀點。大多數受訪者表示,他們對民調的可信度存有疑慮,主要原因是他們擔心政府可能會在調查中進行操控,以符合特定政治目標。

    受訪者還提到,民意調查的結果通常不會對他們的投票意願產生影響。換句話說,他們的選擇通常受到更多因素的影響,例如候選人的政策立場和政府做事的認真與否,而不是單純依賴民調結果。

    從訪問中我們可以得出的結論是,大多數民眾對民調持謹慎態度,並認為它們對他們的投票決策影響有限。

  98. Wunderbarer Blog! Ich habe es beim Surfen auf Yahoo News gefunden. Haben Sie Vorschläge, wie Sie in Yahoo News gelistet werden? Ich versuche es schon eine Weile, aber ich scheine nie dort anzukommen! Danke

  99. 民意調查是什麼?民調什麼意思?
    民意調查又稱為輿論調查或民意測驗,簡稱民調。一般而言,民調是一種為了解公眾對某些政治、社會問題與政策的意見和態度,由專業民調公司或媒體進行的調查方法。

    目的在於通過網路、電話、或書面等媒介,對大量樣本的問卷調查抽樣,利用統計學的抽樣理論來推斷較為客觀,且能較為精確地推論社會輿論或民意動向的一種方法。
    以下是民意調查的一些基本特點和重要性:

    抽樣:由於不可能向每一個人詢問意見,所以調查者會選擇一個代表性的樣本進行調查。這樣本的大小和抽樣方法都會影響調查的準確性和可靠性。
    問卷設計:為了確保獲得可靠的結果,問卷必須經過精心設計,問題要清晰、不帶偏見,且易於理解。
    數據分析:收集到的數據將被分析以得出結論。這可能包括計算百分比、平均值、標準差等,以及更複雜的統計分析。
    多種用途:民意調查可以用於各種目的,包括政策制定、選舉預測、市場研究、社會科學研究等。
    限制:雖然民意調查是一個有價值的工具,但它也有其限制。例如,樣本可能不完全代表目標人群,或者問卷的設計可能導致偏見。
    影響決策:民意調查的結果常常被政府、企業和其他組織用來影響其決策。
    透明度和誠實:為了維護調查的可信度,調查組織應該提供其調查方法、樣本大小、抽樣方法和可能的誤差範圍等詳細資訊。
    民調是怎麼調查的?
    民意調查(輿論調查)的意義是指為瞭解大多數民眾的看法、意見、利益與需求,以科學、系統與公正的資料,蒐集可以代表全部群眾(母體)的部分群眾(抽樣),設計問卷題目後,以人工或電腦詢問部分民眾對特定議題的看法與評價,利用抽樣出來部分民眾的意見與看法,來推論目前全部民眾的意見與看法,藉以衡量社會與政治的狀態。

    以下是進行民調調查的基本步驟:

    定義目標和目的:首先,調查者需要明確調查的目的。是要了解公眾對某個政策的看法?還是要評估某個政治候選人的支持率?
    設計問卷:根據調查目的,研究者會設計一份問卷。問卷應該包含清晰、不帶偏見的問題,並避免導向性的語言。
    選擇樣本:因為通常不可能調查所有人,所以會選擇一部分人作為代表。這部分人被稱為“樣本”。最理想的情況是使用隨機抽樣,以確保每個人都有被選中的機會。
    收集數據:有多種方法可以收集數據,如面對面訪問、電話訪問、郵件調查或在線調查。
    數據分析:一旦數據被收集,研究者會使用統計工具和技術進行分析,得出結論或洞見。
    報告結果:分析完數據後,研究者會編寫報告或發布結果。報告通常會提供調查方法、樣本大小、誤差範圍和主要發現。
    解釋誤差範圍:多數民調報告都會提供誤差範圍,例如“±3%”。這表示實際的結果有可能在報告結果的3%範圍內上下浮動。
    民調調查的質量和可信度很大程度上取決於其設計和實施的方法。若是由專業和無偏見的組織進行,且使用科學的方法,那麼民調結果往往較為可靠。但即使是最高質量的民調也會有一定的誤差,因此解讀時應保持批判性思考。

    為什麼要做民調?
    民調提供了一種系統性的方式來了解大眾的意見、態度和信念。進行民調的原因多種多樣,以下是一些主要的動機:

    政策制定和評估:政府和政策制定者進行民調,以了解公眾對某一議題或政策的看法。這有助於制定或調整政策,以反映大眾的需求和意見。
    選舉和政治活動:政黨和候選人通常使用民調來評估自己在選舉中的地位,了解哪些議題對選民最重要,以及如何調整策略以吸引更多支持。
    市場研究:企業和組織進行民調以了解消費者對產品、服務或品牌的態度,從而制定或調整市場策略。
    社會科學研究:學者和研究者使用民調來了解人們的社會、文化和心理特征,以及其與行為的關係。
    公眾與媒體的期望:民調提供了一種方式,使公眾、政府和企業得以了解社會的整體趨勢和態度。媒體也經常報導民調結果,提供公眾對當前議題的見解。
    提供反饋和評估:無論是企業還是政府,都可以透過民調了解其表現、服務或政策的效果,並根據反饋進行改進。
    預測和趨勢分析:民調可以幫助預測某些趨勢或行為的未來發展,如選舉結果、市場需求等。
    教育和提高公眾意識:通過進行和公布民調,可以促使公眾對某一議題或問題有更深入的了解和討論。

    民調可信嗎?
    民意調查的結果數據隨處可見,尤其是政治性民調結果幾乎可說是天天在新聞上放送,對總統的滿意度下降了多少百分比,然而大家又信多少?

    在景美市場的訪問中,我們了解到民眾對民調有一些普遍的觀點。大多數受訪者表示,他們對民調的可信度存有疑慮,主要原因是他們擔心政府可能會在調查中進行操控,以符合特定政治目標。

    受訪者還提到,民意調查的結果通常不會對他們的投票意願產生影響。換句話說,他們的選擇通常受到更多因素的影響,例如候選人的政策立場和政府做事的認真與否,而不是單純依賴民調結果。

    從訪問中我們可以得出的結論是,大多數民眾對民調持謹慎態度,並認為它們對他們的投票決策影響有限。

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  101. Sight Care is a daily supplement proven in clinical trials and conclusive science to improve vision by nourishing the body from within. The SightCare formula claims to reverse issues in eyesight, and every ingredient is completely natural.

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