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9 votes
2 answers
2k views

Automating statistical correlation between "texts" and "data"

I am collecting textual data surrounding press releases, blog posts, reviews, etc of certain companies' products and performance. Specifically, I am looking to see if there are correlations between ...
warren's user avatar
  • 193
17 votes
12 answers
34k views

Best books for an introduction to statistical data analysis?

I bought this book: How to Measure Anything: Finding the Value of Intangibles in Business and Head First Data Analysis: A Learner's Guide to Big Numbers, Statistics, and Good Decisions What ...
14 votes
4 answers
7k views

Best ways to aggregate and analyze data

Having just recently started teaching myself Machine Learning and Data Analysis I'm finding myself hitting a brick wall on the need for creating and querying large sets of data. I would like to take ...
Justin Bozonier's user avatar
34 votes
7 answers
4k views

How do you convey the beauty of the Central Limit Theorem to a non-statistician?

My father is a math enthusiast, but not interested in statistics much. It would be neat to try to illustrate some of the wonderful bits of statistics, and the CLT is a prime candidate. How would you ...
5 votes
2 answers
8k views

Where is a good place to find survey results?

Sites like eMarketer offer general survey results about internet usage. Who else has a big set of survey results, or regularly releases them? Preferably marketing research focused. Thanks!
10 votes
4 answers
2k views

Calculating ratio of sample data used for model fitting/training and validation

Provided a sample size "N" that I plan on using to forecast data. What are some of the ways to subdivide the data so that I use some of it to establish a model, and the remainder data to validate the ...
dassouki's user avatar
  • 1,449
6 votes
4 answers
6k views

Incorporating boolean data into analysis

I have a data set of about 3,000 field observations. The data collected is divided into 20 variables (real numbers), 30 boolean variables, and 10 or so look up variables and one "answer" variable ...
dassouki's user avatar
  • 1,449
60 votes
3 answers
46k views

Standard deviation of standard deviation

What is an estimator of standard deviation of standard deviation if normality of data can be assumed?
user avatar
3 votes
1 answer
467 views

Forecasting handbooks

In engineering, we usually have Handbooks that pretty much dictate the state of the practice. These books are usually devoid of theory and focus on the applied methodology. Is there a forecasting ...
71 votes
2 answers
31k views

What is the difference between a partial likelihood, profile likelihood and marginal likelihood?

I see these terms being used and I keep getting them mixed up. Is there a simple explanation of the differences between them?
Rob Hyndman's user avatar
  • 57.5k
41 votes
12 answers
11k views

Open Source statistical textbooks?

There have been a few questions about statistical textbooks, such as the question Free statistical textbooks. However, I am looking for textbooks that are Open Source, for example, having an Creative ...
72 votes
8 answers
61k views

Is PCA followed by a rotation (such as varimax) still PCA?

I have tried to reproduce some research (using PCA) from SPSS in R. In my experience, principal() function from package psych ...
Roman Luštrik's user avatar
28 votes
1 answer
2k views

How can one empirically demonstrate in R which cross-validation methods the AIC and BIC are equivalent to?

In a question elsewhere on this site, several answers mentioned that the AIC is equivalent to leave-one-out (LOO) cross-validation and that the BIC is equivalent to K-fold cross validation. Is there ...
russellpierce's user avatar
7 votes
2 answers
823 views

Why prediction of a predicted variable from a discriminant analysis is imperfect

I am puzzled by something I found using Linear Discriminant Analysis. Here is the problem - I first ran the Discriminant analysis using 20 or so independent variables to predict 5 segments. Among the ...
chi-square's user avatar
4 votes
2 answers
365 views

Heuristics for optimizing ν-SVM?

Do you know any good heuristics for finding optimal value of ν in case of ν-SVM classification? In this particular problem I have a radial basis kernel, if it helps.
user avatar
4 votes
2 answers
1k views

Something like E-M for discriminative models?

E-M provides a way to improve the estimation of a generative model with unannotated data. Is there anything out there that works the same way for discriminative models (e.g. perceptrons)? For example, ...
bmargulies's user avatar
18 votes
1 answer
703 views

E-M, is there an intuitive explanation?

The E-M procedure appears, to the uninitiated, as more or less black magic. Estimate parameters of an HMM (for example) using supervised data. Then decode untagged data, using forward-backward to '...
bmargulies's user avatar
4 votes
1 answer
380 views

To what extent can we call a Geometric Distribution a Geometric Density [duplicate]

In some papers, for example in "The Geometric Density with Unknown Location Parameter" by Klotz, a Geometric Distribution is called a Geometric Density. For me, this claim looks erroneous, however ...
Peter Smit's user avatar
  • 2,068
22 votes
2 answers
28k views

What are the differences between the Baum-Welch algorithm and Viterbi training?

I am currently using Viterbi training for an image segmentation problem. I wanted to know what the advantages/disadvantages are of using the Baum-Welch algorithm instead of Viterbi training.
Mykie's user avatar
  • 511
291 votes
13 answers
258k views

Is there any reason to prefer the AIC or BIC over the other?

The AIC and BIC are both methods of assessing model fit penalized for the number of estimated parameters. As I understand it, BIC penalizes models more for free parameters than does AIC. Beyond a ...
russellpierce's user avatar
20 votes
5 answers
25k views

Post-hocs for within subjects tests?

What is the preferred method for for conducting post-hocs for within subjects tests? I've seen published work where Tukey's HSD is employed but a review of Keppel and Maxwell & Delaney suggests ...
russellpierce's user avatar
12 votes
2 answers
2k views

How to understand a convolutional deep belief network for audio classification?

In "Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations" by Lee et. al.(PDF) Convolutional DBN's are proposed. Also the method is evaluated for image ...
Peter Smit's user avatar
  • 2,068
15 votes
4 answers
1k views

What graphical techniques are used in Structural Equation Modeling?

I'm curious if there are graphical techniques particular, or more applicable, to structural equation modeling. I guess this could fall into categories for exploratory tools for covariance analysis or ...
ars's user avatar
  • 13k
57 votes
4 answers
101k views

What is difference-in-differences?

Difference in differences has long been popular as a non-experimental tool, especially in economics. Can somebody please provide a clear and non-technical answer to the following questions about ...
Graham Cookson's user avatar
47 votes
4 answers
15k views

What is an instrumental variable?

Instrumental variables are becoming increasingly common in applied economics and statistics. For the uninitiated, can we have some non-technical answers to the following questions: What is an ...
Graham Cookson's user avatar
14 votes
5 answers
6k views

When to use multiple models for prediction?

This is a fairly general question: I have typically found that using multiple different models outperforms one model when trying to predict a time series out of sample. Are there any good papers ...
Shane's user avatar
  • 12.5k
18 votes
4 answers
1k views

Comprehensive overview of loss functions?

I am trying to get a global perspective on some of the essential ideas in machine learning, and I was wondering if there is a comprehensive treatment of the different notions of loss (squared, log, ...
John L. Taylor's user avatar
104 votes
5 answers
16k views

Why is ANOVA taught / used as if it is a different research methodology compared to linear regression?

ANOVA is equivalent to linear regression with the use of suitable dummy variables. The conclusions remain the same irrespective of whether you use ANOVA or linear regression. In light of their ...
user avatar
10 votes
1 answer
4k views

How can I use optimal scaling to scale an ordinal categorical variable?

In an answer to this question about treating categorical data as continuous, optimal scaling was mentioned. How does this method work and how is it applied?
Freya Harrison's user avatar
65 votes
8 answers
60k views

Does it ever make sense to treat categorical data as continuous?

In answering this question on discrete and continuous data I glibly asserted that it rarely makes sense to treat categorical data as continuous. On the face of it that seems self-evident, but ...
walkytalky's user avatar
  • 1,918
105 votes
17 answers
73k views

Under what conditions does correlation imply causation?

We all know the mantra "correlation does not imply causation" which is drummed into all first year statistics students. There are some nice examples here to illustrate the idea. But sometimes ...
Rob Hyndman's user avatar
  • 57.5k
14 votes
5 answers
13k views

What ways are there to show two analytical methods are equivalent?

I have two different analytical methods that can measure the concentration of a particular molecule in a matrix (for instance measure the amount of salt in water) The two methods are different, and ...
PaulHurleyuk's user avatar
  • 1,599
10 votes
2 answers
559 views

Does the cross validation implementation influence its results?

As you know, there are two popular types of cross-validation, K-fold and random subsampling (as described in Wikipedia). Nevertheless, I know that some researchers are making and publishing papers ...
user avatar
13 votes
3 answers
889 views

Is there a standard technique to debug MCMC programs?

Debugging MCMC programs is notoriously difficult. The difficulty arises because of several issues some of which are: (a) Cyclic nature of the algorithm We iteratively draw parameters conditional on ...
user avatar
30 votes
3 answers
31k views

Unsupervised, supervised and semi-supervised learning

In the context of machine learning, what is the difference between unsupervised learning supervised learning and semi-supervised learning? And what are some of the main algorithmic approaches to ...
Ami's user avatar
  • 978
32 votes
4 answers
25k views

What is the best method for checking convergence in MCMC?

What is your preferred method of checking for convergence when using Markov chain Monte Carlo for Bayesian inference, and why?
Graham Cookson's user avatar
22 votes
5 answers
699 views

When can you use data-based criteria to specify a regression model?

I've heard that when many regression model specifications (say, in OLS) are considered as possibilities for a dataset, this causes multiple comparison problems and the p-values and confidence ...
Statisfactions's user avatar
2 votes
5 answers
15k views

In SAS, how do you copy & paste from the output window?

Sometimes, I just want to do a copy & paste from the output window in SAS. I can highlight text with a mouse-drag, but only SOMETIMES does that get copied to the clipboard. It doesn't matter if I ...
Baltimark's user avatar
  • 2,288
13 votes
6 answers
1k views

Dubious use of signal processing principles to identify a trend

I am proposing to try and find a trend in some very noisy long term data. The data is basically weekly measurements of something which moved about 5mm over a period of about 8 months. The data is to ...
Ian Turner's user avatar
31 votes
6 answers
18k views

Variable selection procedure for binary classification

What are the variable/feature selection that you prefer for binary classification when there are many more variables/feature than observations in the learning set? The aim here is to discuss what is ...
49 votes
5 answers
93k views

Negative values for AICc (corrected Akaike Information Criterion)

I have calculated AIC and AICc to compare two general linear mixed models; The AICs are positive with model 1 having a lower AIC than model 2. However, the values for AICc are both negative (model 1 ...
Freya Harrison's user avatar
59 votes
19 answers
9k views

Mathematical Statistics Videos

A question previously sought recommendations for textbooks on mathematical statistics Does anyone know of any good online video lectures on mathematical statistics? The closest that I've found are: ...
14 votes
3 answers
6k views

Is it valid to aggregate a time series to make it look more meaningful?

Another question about time series from me. I have a dataset which gives daily records of violent incidents in a psychiatric hospital over three years. With the help from my previous question I have ...
Chris Beeley's user avatar
  • 5,831
21 votes
2 answers
4k views

How does random forest generate the random forest

I am not an expert of random forest but I clearly understand that the key issue with random forest is the (random) tree generation. Can you explain me how the trees are generated? (i.e. What is the ...
robin girard's user avatar
  • 6,755
10 votes
4 answers
1k views

Good line color for "threshold" line in a time-series graph?

We're plotting time-series metrics in the context of network/server operations. The data has a 5-minute sample rate, and consists of things like CPU utilization, error rate, etc. We're adding a ...
MikeF's user avatar
  • 203
26 votes
6 answers
71k views

Always Report Robust (White) Standard Errors?

It has been suggested by Angrist and Pischke that Robust (i.e. robust to heteroskedasticity or unequal variances) Standard Errors are reported as a matter of course rather than testing for it. Two ...
Graham Cookson's user avatar
384 votes
84 answers
183k views

What is your favorite "data analysis" cartoon?

Data analysis cartoons can be useful for many reasons: they help communicate; they show that quantitative people have a sense of humor too; they can instigate good teaching moments; and they can help ...
108 votes
32 answers
39k views

What book would you recommend for non-statistician scientists?

What book would you recommend for scientists who are not statisticians? Clear delivery is most appreciated. As well as the explanation of the appropriate techniques and methods for typical tasks: ...
36 votes
4 answers
11k views

Why isn't RANSAC most widely used in statistics?

Coming from the field of computer vision, I've often used the RANSAC (Random Sample Consensus) method for fitting models to data with lots of outliers. However, I've never seen it used by ...
Bossykena's user avatar
  • 687
63 votes
6 answers
22k views

Introduction to statistics for mathematicians

What is a good introduction to statistics for a mathematician who is already well-versed in probability? I have two distinct motivations for asking, which may well lead to different suggestions: I'd ...

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