Heidi Hammel Quotes

Statistics is the plural of anecdote.

All too often when liberals cite statistics, they forget the statisticians' warning that correlation is not causation.

If you're a social scientist worth your salt, you never do a univariate analysis.

Every time I think that political analysts and writers will finally recognize that most of them don't understand much about political polls, they prove me wrong. They don't know how to read them; they don't understand the importance of cross tabs within a given poll, and they don't know how to analyze them.

We should be cautious about embracing data before it is published in the academic press, and must always avoid treating correlation as causation.

If one in twenty does not seem high enough odds, we may, if we prefer it, draw the line at one in fifty (the 2 per cent. point), or one in a hundred (the 1 per cent. point). Personally, the writer prefers to set a low standard of significance at the 5 per cent. point, and ignore entirely all results which fail to reach this level. A scientific fact should be regarded as experimentally established only if a properly designed experiment rarely fails to give this level of significance.

Much of what I do in my job is think about whether relationships we see in data are causal, as opposed to just reflecting correlations. It's exactly these issues which come up in evaluating studies in public health.

There was a danger that skeptics and opponents would misread those likelihood ratio tests as rejections of an entire class of models, which of course they were not.

If your experiment needs statistics, you ought to have done a better experiment.

Statistics is the grammar of science.

Definition of a Statistician: A man who believes figures don't lie, but admits than under analysis some of them won't stand up either.

The best scientific way to discover if one factor influences another is to do a controlled experiment.

I think the biggest problem in clinical trials is that they are underpowered. And that fundamentally, the studies are just too small.

To understand God’s thoughts we must study statistics, for these are the measure of his purpose.

The big mystery of Big Data is causation versus correlation.

Some people hate the very name of statistics, but I find them full of beauty and interest. Whenever they are not brutalized, but delicately handled by the higher methods, and are warily interpreted, their power of dealing with complicated phenomena is extraordinary. They are the only tools by which an opening can be cut through the formidable thicket of difficulties that bars the path of those who pursue the Science of Man.

The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of data.

Our polling methodology has gotten outdated, and, in fact, it's not really telling us what it needs to be telling us.

Biases and blind spots exist in big data as much as they do in individual perceptions and experiences. Yet there is a problematic belief that bigger data is always better data and that correlation is as good as causation.

Obviously it's a statistics game.

I have never had an interest in opinion polls. They are merely an indicator, that's all.

I'm not too worried about stats and stuff like that.

Statistics are there to be broken.

Numbers can't speak for themselves, and data sets - no matter their scale - are still objects of human design.

[Coining phrase "null hypothesis"] In relation to any experiment we may speak of this hypothesis as the "null hypothesis," and it should be noted that the null hypothesis is never proved or established, but is possibly disproved, in the course of experimentation. Every experiment may be said to exist only in order to give the facts a chance of disproving the null hypothesis.