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### Prediction vs. Explanation and its Effect on Statistical Methods [duplicate]

In layman's terms, what is the difference between predicting and explaining in statistics? I was looking for the differences between AIC and BIC and found this post with an answer stating: My quick ...
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### Practical thoughts on explanatory vs predictive modeling [duplicate]

Possible Duplicate: Practical thoughts on explanatory vs. predictive modeling This question has been bugging me for some time, and I was going to write a blog post about it. However, I think it ...
155k views

### The Two Cultures: statistics vs. machine learning?

Last year, I read a blog post from Brendan O'Connor entitled "Statistics vs. Machine Learning, fight!" that discussed some of the differences between the two fields. Andrew Gelman responded favorably ...
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### Recommendations for non-technical yet deep articles in statistics

The inspiration for this question comes from the late Leo-Breiman's well-known article Statistical Modeling: The Two Cultures (available open access). The author compares what he sees as two disparate ...
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### Family-wise error boundary: Does re-using data sets on different studies of independent questions lead to multiple testing problems?

If a team of researchers perform multiple (hypothesis) tests on a given data set, there is a volume of literature asserting that they should use some form of correction for multiple testing (...
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### Model Selection in Propensity Score Matching

I am trying to fit a logistic model to create propensity scores. Looking though the literature, there appears to be some disagreement on which covariates to include when designing such a model. Some ...
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### A fundamental question about multivariate regression

This is slightly embarrassing, as I've done a fair amount of statistical work, but for years I've heard this niggling voice at the back of my head, and I need to ask someone. I remember when I first ...
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### Purpose of leave-one-out cross-validation in descriptive modelling

I refer you to Breiman's paper Statistical Modeling - A Tale of Two Cultures where he illustrated some examples of descriptive modelling. Under section 11.1, 100 runs of regression were performed, ...
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### Significance of epidemiological confounders in a generalized linear model

I am identifying risk factors for children snoring among several predictors with generalized linear model. With backward selection, age and sex do not appear to be significant so I removed them from ...
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### How to do goodness-of-fit and residual diagnosis for rlm in R?

I am reading What are common statistical sins?, and especially @jebyrnes answer: Failing to test the assumption that error is normally distributed and has constant variance between treatments. ...
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### mixed model: is it primarily used for prediction or explanation or both?

Inspired by this post on the difference between explaining and predicting. I want to ask is mixed model primarily used to get better explanation (such as, but not limited to, getting better ...
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### Manual vs automated approach for predictive modeling

Many statistics textbooks emphasise a manual modeling design approach, whereby the practictioner performs exploratory analysis by hand to assess several factors including whether there's any ...
156 views

### Regression: Causation vs Prediction vs Description

In my experience it seems me that the interpretation about regression, its meaning and its scope, are debatable and great confusion exist about those things. It seems me that confusions are not go ...