# Tagged Questions

A way of re-expressing data to make their values lie between 0 and 1 (or 0% and 100%).

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### How can two different experiments be compared when they have different controls?

Experiment 1: mice of genotype1 compared to their wild type littermates, Experiment 2: mice of genotype2 compared to their wild type littermates. (Each experiment in its own right is pretty ...
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### Do I need to rescale dummy variables for PCA?

I am wondering if for a PCA for which I rescale my numeric variables, I need to rescale my dummy variables as well ? I have read on the internet that I should not but I do not see why. I guess the ...
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### Denormalize value after prediction

I don't know how to denormalize (0-1 normalized) data after prediction. I have 1 output and several input values. It's clear for 1 input I must use min and max value previously used for normalization. ...
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### Creating a Normalization Factor

I have a relatively simple problem that I can't seem to find a satisfactory solution to. If I have three scales for three different sets of data. One varies from [-5,5] the other from [1,10], and ...
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### Normalization in SVM

I have applied libsvm with a linear kernel to a set of instances and I have obtained a 68 % success: ...
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### Normalization and hypothesis testing under system equations

Hypothesis testing under single equation linear regression is robust to simple data normalization (for example dividing all variables by their respective mean). I see that the same is true for systems ...
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### Normalize a periodic parameter

I am using inverse modelling software (PEST) to estimate a periodic parameter for the direction of anisotropy, $\hat{\theta}$, which is somewhere in $[0^{\circ}, 180^{\circ})$ (i.e., has a wavelength ...
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### how to Normalize data(with noise) into 0-1 range good scale in mean and variance?

i have a matrix data. Perhaps some data in one cluster and another in some cluster. data scale is between [0-1000](just example). and i want to normalize into [0-1] and good in mean and variance. it ...
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### Standard score (z-transformation) normalization or 0-1 normalization, which one is better for k-NN?

I am not much experienced in data mining, but I know that I should normalize my data before running k-NN classifier on it, to have reasonable results. But I found out, that there are many methods to ...
268 views

### Comparing the result of a study which has unequal group sizes

I have conducted two user studies and in my studies I didn't have control over the group sizes. In each study users were put in groups and they were asked to perform some group activities. Here is the ...
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### Alignment and comparison of two unimodal and one uniformly distributed datasets

This question is similar to the following question: Normalize 3 irregulary distributed datasets and make their datapoints statistically relevant to each other describes similar problem, but is more ...
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### Normalize vector-based integer data

I'll preface my question by saying I have a very limited knowledge of statistics, and while I've put some thought into this problem, I'm a bit stuck! Onwards... I have a collection of fixed-size ...
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### Normalize 3 irregulary distributed datasets and make their datapoints statistically relevant to each other

A very practical case. I have 3 parallel inputs/aka data-sets, or you may also call it: A large set of learn cases, each one having 3 parameters/inputs (A, B and C) All 3 inputs have the same ...
172 views

### How to combine unbound variables with very different frequency distributions?

I want to combine three unbound variables. Each variable is the score provided by three different algorithms. Each algorithm predicts the likelihood (score) that a specific interaction between two ...
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### Perform feature normalization before or within model validation?

A common good practice in Machine Learning is to do feature normalization or data standardization of the predictor variables, that's it, center the data substracting the mean and normalize it dividing ...
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### Name of a tool to find out the best power to use in order to normalize a variable

It should be an easy question. I am looking for the name of a tool. It is used to normalize a variable with the best possible power. I think it uses an iterative process to find out this best power. ...
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I want to perform quadrat count analysis on several point processes (or one marked point process), to then apply some dimensionality reduction techniques. The marks are not identically distributed, ...
51 views

### Approximation of partition function (normalizer)

Say we have a nasty probability distribution like, $$P(x) = \frac{P^*(x)}{Z}$$ where we can easily compute $P^*(x)$ for a given $x$ but not $P(x)$ because partition function $Z$ is expensive to ...
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### How to compensate for small errors that could greatly distort observed ratios?

Lets say for two samples, treatment and control, there are three constituent molecules each and their corresponding amounts are as follows: ...
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### Standardizing response variable in shrinkage/regularization

I know that I should standardize my predictors before estimating something like Lasso. But what about the response variable? Do I standardise this as well? Only ...
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### Percentile rank transforming z-scores

I have been looking through methods to convert z-scores to positive values, without taking absolute values and somehow taking the sign of the score into account (I avoided taking absolute value, ...
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### Expectation under similar distribution to inverse Gaussian

I have the following integral that I wish to evaluate: $\int_0^\infty x\,\, p(x)dx$. Where, $p(x)\propto \exp\left(-ax+\frac{b}{x+k}\right)$ for $a,b\ge0$ Firstly what would the normalising constant ...
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### Transformation to normality for random variables with different locations

I have a (potentially infinite) sequence of random variables $X_i$, with $i = 1, 2, \dots$, which have the same distribution (in terms of "shape"), but different locations. I have a sample of size ...
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### MANOVA multivariate normality

I'm running some analysis of student data and I'm having some questions regarding multivariate normality assumption of MANOVA. Should it be done using values of dependent variables or their residuals? ...
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### Data normalization and sufficient statistic

I was taught that when we feed our data to machine learning algorithm (e.g. SVM), we should first normalize our data. Suppose I have a set of data $X = \{x_1,x_2,...,x_n\}$, I knew two-way of ...
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### Sum of the samples as the normalising factor in MCMC?

Suppose using an specific sampling method I have generated a sample but I now want the normalising factor to be able to calculate the probabilities. Can I consider the sum of the values as their ...
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### Normalizing when doing count statistics of patient numbers on different arms of a clinical trial

I'm looking at clinical trial data where there are various numbers of patients on different arms (A, B, C, D). All arms receive a drug that is known to cause a toxicity, but some arms receive an ...
177 views

### Box-Cox transformation for residuals in R

I have residuals for my model. They are simply measured-predicted. However, I notice that they do not follow a normal distribution. I want to make my residuals distribution normal so that I can ...
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### Normalization to control

Given two experimental runs, each with an experimental & a control group, I would like to test for a statistically significant difference between the first and second experimental group (using ...