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如何发现图表中的误导性信息 – 译学馆
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如何发现图表中的误导性信息

How to spot a misleading graph - Lea Gaslowitz

一牙膏品牌宣称其产品可去除的
A toothpaste brand claims their product will destroy more plaque
牙菌斑比别的多
than any product ever made.
政客们总是承诺用他们的计划能创造出最多的工作机会
A politician tells you their plan will create the most jobs.
对于广告和政治中的这些夸大之词
We’re so used to hearing these kinds of exaggerations
我们早已司空见惯
in advertising and politics
连眼睛也懒得眨一下
that we might not even bat an eye.
但如果这些说辞有图表作证呢?
But what about when the claim is accompanied by a graph?
图表不代表观点
Afterall, a graph isn’t an opinion.
而是现实直白的数字 谁能与数字争辩呢?
It represents cold, hard numbers, and who can argue with those?
事实却是 图表的误导操控作用 有多种方式实现
Yet, as it turns out, there are plenty of ways graphs can mislead
且明目张胆
and outright manipulate.
这里提一些值得注意的地方
Here are some things to look out for.
1992年 雪佛兰试图用这张图表证明自身
In this 1992 ad, Chevy claimed to make the most reliable trucks in America
卡车的可靠性最高
using this graph.
不仅表明过去10年卖出卡车中的
Not only does it show that 98% of all Chevy trucks sold in the last ten years
98%仍在被使用
are still on the road,
也似乎表明比丰田可靠性高出两倍
but it looks like they’re twice as dependable as Toyota trucks.
但是 只要仔细看下竖轴上的数字
That is, until you take a closer look at the numbers on the left
就会发现本田的数据约是96.5%
and see that the figure for Toyota is about 96.5%.
刻度只从95到100%
The scale only goes between 95 and 100%.
如果改为0到100 图表就会成这样
If it went from 0 to 100, it would look like this.
歪曲刻度 是图表歪曲数据事实的
This is one of the most common ways graphs misrepresent data,
最常见方法
by distorting the scale.
放大y轴上原先比例较小的部分
Zooming in on a small portion of the y-axis
产生的差距就明显可见了
exaggerates a barely detectable difference between the things being compared.
柱状图误导性尤其大
And it’s especially misleading with bar graphs
因为通过柱状图的高低 我们作出判断
since we assume the difference in the size of the bars
高低差代表数值差
is proportional to the values.
同样 x轴上的刻度也会不均匀
But the scale can also be distorted along the x-axis,
通常出现在线状图中 表明随时间变化的趋势
usually in line graphs showing something changing over time.
这张图说明 美国2008至2010年失业率的上升
This chart showing the rise in American unemployment from 2008 to 2010
从两方面控制了x轴
manipulates the x-axis in two ways.
首先 刻度不均匀
First of all, the scale is inconsistent,
2009年3月后的15个月被压缩
compressing the 15-month span after March 2009
比之前的6个月刻度短
to look shorter than the preceding six months.
使用均匀数据点后 表格走势大不一样
Using more consistent data points gives a different picture
显示2009年末逐渐下降
with job losses tapering off by the end of 2009.
如果你对一开始的连续上升感到奇怪
And if you wonder why they were increasing in the first place,
看看时间轴的起点 即美国最严重的经济危机
the timeline starts immediately after the U.S.’s biggest financial collapse
“大萧条”时代
since the Great Depression.
这些把戏被称为“最佳图表显示”
These techniques are known as cherry picking.
一个时间段可能被精心挑出 并刚好将某一主要
A time range can be carefully chosen to exclude the impact of a major event
事件影响排除在外
right outside it.
并且 选择具体数据点也会将这一时段的重大变化隐藏
And picking specific data points can hide important changes in between.
即使图表本身并无错误
Even when there’s nothing wrong with the graph itself,
相关数据遗漏也会给人造成错觉
leaving out relevant data can give a misleading impression.
这张表显示每年看“超级碗”比赛的人数
This chart of how many people watch the Super Bowl each year
表面上这一赛事的受欢迎程度爆炸式增长
makes it look like the event’s popularity is exploding.
但人口增长并未算在内
But it’s not accounting for population growth.
实际受欢迎度相对稳定
The ratings have actually held steady
虽然球迷数量增加
because while the number of football fans has increased,
整体观看率却并未随之增加
their share of overall viewership has not.
总之 如果事先不了解
Finally, a graph can’t tell you much
图表解释的问题 那么一张图能表达的并不多
if you don’t know the full significance of what’s being presented.
这两图都用了来自美国国家环境信息中心
Both of the following graphs use the same ocean temperature data
同样的海水温度数据
from the National Centers for Environmental Information.
为何给人的印象却完全相反?
So why do they seem to give opposite impressions?
第一张借用了1880至2016年
The first graph plots the average annual ocean temperature
年平均海洋温度
from 1880 to 2016,
使得期间温度变化很不明显
making the change look insignificant.
而实际上 即使是升温半摄氏度
But in fact, a rise of even half a degree Celsius
也会给生态带来大规模的破坏
can cause massive ecological disruption.
而第二张
This is why the second graph,
清楚显示了每年平均气温的变化
which show the average temperature variation each year,
意义更为重大
is far more significant.
善加利用 图表能帮我们从根本上了解复杂数据
When they’re used well, graphs can help us intuitively grasp complex data.
但随着可视化程序将更多的图表应用于各类媒体
But as visual software has enabled more usage of graphs throughout all media,
也使其变得更加粗放或具有欺骗意味
it’s also made them easier to use in a careless or dishonest way.
下次再看到图表时
So the next time you see a graph,
不要被它的轴或走势迷惑
don’t be swayed by the lines and curves.
看看横竖轴 数字标法 刻度和所描述的问题
Look at the labels, the numbers, the scale, and the context,
看看它究竟想告诉我们什么
and ask what story the picture is trying to tell.

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不同图表由于作用不同,制作时会加入一些具有特定目的的因素,这些信息具有误导性,怎样辨别呢?

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