# Tagged Questions

Mathematical re-expression, often nonlinear, of data values. Data are often transformed either to meet the assumptions of a statistical model or to make the results of an analysis more interpretable.

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### Out of ideas: transformation of continuous variables to obtain normality of residuals seemingly impossible

I've been browsing stackexchange for days to come up with decent solutions, but to no avail so far. Some threads seem to apply and offer solutions (e.g. How to transform negative data to be ...
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### How to prepare data to analyze two values simultaneously as one

as a newbie in statistics I'm having trouble with preparing my data. I have data where a measure is performed on left and right side. When comparing group means I need to take simultaneously both ...
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### Linear scaling of the observed data prior to fitting a differential equation [on hold]

I am trying to fit a process-based model consisting of a system of first-order ODEs to some data using the modFit function with all defaults enabled from the R package FME. When I use the raw data, ...
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### How to apply Box Cox to train and test data?

I am trying to standardize my data to performing prediction on it. Some of the features in my data are skewed and hence I am applying Box Cox transformation to reduce skewness. My data also ...
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### Recurrent event survival model set-up

I'm trying to model customer reorders using a survival model using R's survival package and am having a hard time figuring out if I'm setting up the data correctly ...
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### Smaller residuals after transformation better?

This is a two part question concerning linear regression in R. Here is my code and what my residual plot looks like before transformation: ...
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### Log transformation for ratio data [closed]

I would like to ask about the transformation of the variable into log form. As far as I know, we usually do not log the interest rate as the variable is already in percentage. How about if the ...
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### One-hot vs dummy encoding in Scikit-learn

There are two different ways to encoding categorical variables. Say, one categorical variable has n values. One-hot encoding converts it into n variables, while dummy encoding converts it into n-1 ...
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### Can I just log transform a dependent variable (to remove heteroscedasticity) without transforming the independent variables in a 3 way ANOVA?

I'm trying to analyse a data set using an ANOVA but have significant heteroscedasticity - transforming the DV using a log-transformation seems to remove this issue, but I wanted to check if I should ...
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### Relational to Dimensional modelling

So, I currently have a relational database, supporting all the business logic of an application. I'm currently evaluating choices to build a basic, yet extensible, business analytics platform, and a ...
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### Data preparation of a new record on the fly [migrated]

I am facing problem in the implementation of Data Preparation of a single record on the fly. I am loading the model from disk and I need to to make prediction against it. Lets Say, I have 3 ...
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### Data Transformation Needed for Logistic Regression?

I'm planning to do logistic regression with my dependent variable as either with injury or no injury with one of my independent variables as average computer use. I have attached a sample ...
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### Data Transformation Question - Multiplying data proportional to demographics

I have a bunch of data that is tied to demographic variables (Age, Sex, Income, Education, etc.). However, the data is sent by one person in a household for the entire house. It's numerical data and I ...
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### Merging information of several events

I'm working in a database related to endometrium ultrasound. My DB contains several columns that may describe one or more injuries (scar tissues) by dimensions and volume: Injury1Height, Injury1Width, ...
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### Quantile of function of random variable

Given a continuous analytical function $g(x)$ of the continuous random variable $x$, the CDF and PDF $F_x(x),f_x(x)$ and the quantile function $F^{-1}_x(t)$ of $x$, is it possible to find a closed ...
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### When I transform a distribution to apply a test that assumes normality, is the transformation “lossless”?

Many times we deal with data that do not conform to assumptions of normality and/or homoscedasticity/homogeneity of variance. Yet the reality is that almost all analyses benefit from improved the ...
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### Log transform in time series

After taking the $\log(1+x)$ transformation on a time series, I am guessing which features should I use as predictors: $\text{mean}(\log(1+x))$ vs $\log(1+\text{mean}(x))$ $\text{std}(\log(1+x))$ vs ...
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### How do you interpret a percent variable with a log-transformed outcome?

It doesn't make sense to log transform my x-variable (for a more intuitive elasticity interpretation), since it is already in a % format, but with a log transformed outcome: ln(y) = B0 + B1X1 where ...
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### Looking for public data set with long tailed predictor [closed]

I am looking for some public data set in health science with long tailed predictor and binary outcome. If you happen to see one of them, could you please let me know? Thanks in advance!
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### Nonlinear Multiple Regression

I have a dataset that has multiple x predictor values. To fit a model, I was going to use multiple regression but I looked at the scatter plots for each x value and the y dependent variable and they ...
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### Transformation of a regression coefficient when independent variable was log-transdormed

In the context of a linear regression model where the independent variable ($X$) was log-transformed, like: $Y = \alpha + \beta·ln(X)$ Is there a straightforward way to transform a regression ...
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### Appropriate data transformation

I have two dependent variables y1 and y2 with highly skewed distributions. In order to do ANOVA, I was trying to transform the ...
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### Feature Transform - Low Dimensional transformation

Problem High-Description Solved a question about feature transformation but I'm unsure if it's correct. I'm also unsure how to prove the dimension in mathematical formulas. It's about Feature ...
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### Robust estimation of multivariate reference bands

I have a subjectivly healthy population of approx 1200 individuals with three measurements on the continous scale, we can call them y1, y2 and y3. All of these are strongly related to age in a non-...
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### time stamp as input variable for regression (feature extraction)

I am working on web logs and have a time-stamp variable in the format dd-mm-yyyy hh-mm-ss. I have earlier worked on date variable and found that best way to extract feature from date is to create ...
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### What are some of the more popular variable transformations and why/when are they used (to handle what types of distribution problems)?

Like the title states, I'm interested in learning about the more popular data transformation techniques. I know the internet is abound in this information, but I'd like to hear from those working ...
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### Categorical PCA: Merge categories based on Transformation Plots?

A tutorial on categorical pca (CATPCA) (Linting et al. 2012) explains that a decision to merge categories of an ordinal variable can be made based on the category quantification ("none of the ...
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### How to segment hours of audio for speech recognition?

I have 36 hours of speech data along with transcription. I'm planning to have 7 second audio segments, because I don't know any better. Suggestions are welcome. These segments will be passed through ...
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### Interpreting the effect of predictor variables on outcome variable when the latter is logit transformed

I apologize if this question is very simple but I have found a lot of information on how to interpret log transformed variables (http://www.ats.ucla.edu/stat/mult_pkg/faq/general/...
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### Imputing skewed variable?

I have a data set with missing values in the IVs. I intend to use MI and in particular PMM for the numerical variables. One of them is very skewed and has many 0s so I can't log tranform it. My ...
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### Shouldn't A/B be correlated with B/A and A*B?

In data mining problems it is common to do variable transformation, sometimes doing pairwise combinations like A/(B+1), B/(A+1) or A*B. Now, let's say after performing transformations the two best ...
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### log transformation logistic regression

I have a logistic regression in which i transformed geographical distance measured in km using a natural log. I've have run the regression, and now i am having trouble how to interpret the findings. ...