Neil McGuigan
  • Member for 11 years, 6 months
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What is your favorite "data analysis" cartoon?
108 votes

This isn't technically a cartoon, but close enough:

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Famous statistical quotations
80 votes

He uses statistics like a drunken man uses a lamp post, more for support than illumination. -- Andrew Lang

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What are common statistical sins?
65 votes

Reporting p-values when you did data-mining (hypothesis discovery) instead of statistics (hypothesis testing).

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Most famous statisticians
54 votes

John Tukey for Fast Fourier Transforms, exploratory data analysis (EDA), box plots, projection pursuit, jackknife (along with Quenouille). Coined the words "software" and "bit".

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Most famous statisticians
Accepted answer
53 votes

Reverend Thomas Bayes for discovering Bayes' theorem

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Most famous statisticians
47 votes

Carl Gauss for least squares estimation.

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What is a standard deviation?
Accepted answer
34 votes

Standard deviation is a number that represents the "spread" or "dispersion" of a set of data. There are other measures for spread, such as range and variance. Here are some example sets of data, and ...

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Famous statistical quotations
31 votes

"The first time I was in a statistics course, I was there to teach it" John Tukey (link)

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Most famous statisticians
29 votes

Francis Galton for discovering statistical correlation and promoting regression.

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What are good basic statistics to use for ordinal data?
Accepted answer
29 votes

A frequency table is a good place to start. You can do the count, and relative frequency for each level. Also, the total count, and number of missing values may be of use. You can also use a ...

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Most famous statisticians
28 votes

Andrey Markov for stochastic processes and markov chains.

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How should outliers be dealt with in linear regression analysis?
28 votes

Sometimes outliers are bad data, and should be excluded, such as typos. Sometimes they are Wayne Gretzky or Michael Jordan, and should be kept. Outlier detection methods include: Univariate -> ...

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Examples for teaching: Correlation does not mean causation
27 votes

Sometimes correlation is enough. For example, in car insurance, male drivers are correlated with more accidents, so insurance companies charge them more. There is no way you could actually test this ...

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Best ways to aggregate and analyze data
Accepted answer
21 votes

If you have large data sets - ones that make Excel or Notepad load slowly, then a database is a good way to go. Postgres is open-source and very well-made, and it's easy to connect with JMP, SPSS and ...

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Recommend some books/articles/guides to enter predictive analytics?
21 votes

There's no need to call it Predictive Analytics :) It already has two names: statistics, and data mining. Beginner Stats Book: Statistics in Plain English Advanced Stats Book: Multivariate Analysis, ...

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Statistical classification of text
20 votes

I recommend these books - they are highly rated on Amazon too: "Text Mining" by Weiss "Text Mining Application Programming", by Konchady For software, I recommend RapidMiner (with the text plugin), ...

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Famous statistical quotations
19 votes

It ain’t what you don’t know that gets you into trouble. It’s what you know for sure that just ain’t so. Mark Twain (okay, so he's not a statistician)

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What is your favorite layman's explanation for a difficult statistical concept?
15 votes

If you carved your distribution (histogram) out of wood, and tried to balance it on your finger, the balance point would be the mean, no matter the shape of the distribution. If you put a stick in the ...

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How do you decide the sample size when polling a large population?
14 votes

Sample size doesn't much depend on the population size, which is counter-intuitive to many. Most polling companies use 400 or 1000 people in their samples. There is a reason for this: A sample size ...

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What is the difference between discrete data and continuous data?
12 votes

Temperatures are continuous. It can be 23 degrees, 23.1 degrees, 23.100004 degrees. Sex is discrete. You can only be male or female (in classical thinking anyways). Something you could represent ...

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What are common statistical sins?
12 votes

My old stats prof had a "rule of thumb" for dealing with outliers: If you see an outlier on your scatterplot, cover it up with your thumb :)

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What are some valuable Statistical Analysis open source projects?
11 votes

RapidMiner for data and text mining

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Can one use multiple regression to predict one principal component (PC) from several other PCs?
Accepted answer
11 votes

A principal component is a weighted linear combination of all your factors (X's). example: PC1 = 0.1X1 + 0.3X2 There will be one component for each factor (though in general a small number are ...

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Where to cut a dendrogram?
11 votes

There isn't really an answer. It's somewhere between 1 and N. However, you can think about it from a profit perspective. For example, in marketing one uses segmentation, which is much like ...

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Statistics interview questions
11 votes

Here is a big data set. What is your plan for dealing with outliers? How about missing values? How about transformations? Can they deal with real-world data?

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Most famous statisticians
11 votes

W. Edwards Deming for promoting statistical process control

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Statistics interview questions
9 votes

How do you prevent over-fitting when you are creating a statistical model? Good answer: cross-validation

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What book would you recommend for non-statistician scientists?
9 votes

Statistics in Plain English is pretty good. 4.5 on Amazon, 11 reviews. Explains ANOVA pretty well too.

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What is the difference between data mining and statistical analysis?
8 votes

Data mining is statistics, with some minor differences. You can think of it as re-branding statistics, because statisticians are kinda weird. It is often associated with computational statistics, i....

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Statistics interview questions
8 votes

How do you numericize something that is not numerical? Example, "Automatic Feature Extraction for Classifying Audio Data" Rationale: Can they figure out how to analyze something statistically that ...

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