Shifting and rescaling data to assure zero mean and unit variance.

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22 views

Outlier removal and standardization of variables

In a multifactor model of stock returns, I am considering several variable $X_1$, $X_2$, ... , $X_n$ as explanatory variable. However, before including the variables in the model, I would like to: ...
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16 views

Standardizing count variables in panel data with overdispersion - R or Stata

I'm running a regression where the dependent (response) variable is a highly dispersed (slightly zero-inflated) count and the explanatory (independent or predictor) variables are continuous, counts as ...
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1answer
32 views

Could standardizing an independent variable cause the t-statistic of the OLS estimate to change?

Lets say we are looking to estimate the following standard OLS regression: $y_{i} = \beta_{0} + \beta_{1}*X_{i} + \beta_{2}*Z_{i} + \epsilon_{i}$ and that we choose to standardize $X$ as: ...
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13 views

Standardized coefficients and IV method

In a multivariate regression, suppose we want to calculate the metric coefficients from the standardized ones. Is the method (standardized coeffcient times standard deviation of the dependent ...
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28 views

Can you combine z scores from similar but non-identical populations?

Suppose you have a group of people estimating the heights of trees. Suppose you have many different types of trees, some trees with a very low height, and others that are very tall. Suppose each ...
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25 views

Scaling/Normalisation or Standardization

I'm working on SVM and ANN classification tools. In order to improve the classification accuracy, I want to know the best or the recommended data-preprocessing, is it scaling/normalisation or ...
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27 views

Standardizing variables for k-means?

I only have two variables and they are on the same scale. However, the variance corresponding to the first variable is approximately 0.609, whereas for the second variable is 0.154. So my question is ...
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1answer
37 views

Comparison of subpopulations: do I need normalisation?

I have a population of people. Each person has one of three characteristics, say X, Y or Z. I want to compare other characteristics of these people, using the characteristics X, Y and Z as a ...
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21 views

multiple linear regression with normalization - how to get non-scaled full covariance matrix

I am doing a quite complicated multiple regression modelling in physics and have a problem how to got back to covariance matrix for non-normalized parameters. I don't know how to calculate the error ...
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2answers
61 views

Z-scores, standardized tests and population means

I have been using z-scores by subtracting the mean (and then dividing by the SD) of the sample, whereas I recently read they actually need to be the population mean and SD. Assuming you are ...
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0answers
26 views

Composite Scores and Standardized Composite Scores t test

I have a set of survey data related to 20 survey questions. Each of these questions represent a variable (Q1, Q2,......
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13 views

Standardizing inputs for CART

I know I do not need to standardize the predictor variables before applying CART but would there be any adverse effects to doing it anyway? I'm comparing CART to a linear regression where I did ...
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13 views

Standardization of data during multilevel analysis

Recently I obsessed about standardization of scores. I am looking into statistical literature to see if standardization of data is OK or not. a brief about standardization: ...
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24 views

About Standardizing Variables

Before data analysis, by $\frac{(X-mean)}{std}$, so the new variables have mean 0 and variance 1, and then compare different variables since then they are on the same measure scale, my question is, ...
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1answer
112 views

Is standardisation before Lasso really necessary?

I have read three main reasons for standardising variables before something such as Lasso regression: 1) Interpretability of coefficients. 2) Ability to rank the ...
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0answers
61 views

Variable Transformation using Cumulative Distribution Function (CDF)

Consider two different data time-series, Data1 and Data2, expressed using inhomogeneous scales (units). Each of these two data series is itself a weighted-average of a bunch of standardized ...
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19 views

what can be inferred from the error plot of my classifier?

I am working on a classification task where I use 12 features. My training set has 400 samples of positive data and 2000+ samples of unlabelled data. While testing has 34 positive samples and 999 ...
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1answer
25 views

Standardising the weights generated from feedforward back propagation NN

I have binary data input to NN. The weights generated by NN are not normalized, i.e., the weights are not the same for every run of the algorithm. How to standardize these weights?
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34 views

Running standardized/unstandardized regression equation on SPSS

I am working on a regression assignment using SPSS. I have raw, centered, and z scores for the data. I already regressed the DV and IV and see the unstandardized and standardized coefficients under ...
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1answer
28 views

Interpreting standardized mean centers in a cluster

I created a $k$-means with 3 clusters. Some of the variables had a big scale, so I used a $z$-score to standardize them. The others (mostly dummies), I left as is. Now, when I create the table of all ...
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32 views

prerequisites for z-standardization

I tried to search for an answer to this but I was not successful in finding a good one. I wanted to compare data from two modalities together (an EMG reflex and self-rating). I found that in the ...
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0answers
40 views

Standardize continuous predictor variables on [0, 1] scale?

I'm working on a health care regression model predicting # of inpatient visits. My analysis dataset includes a number of hybrid continuous/categorical predictor variables which can hold values on a 0 ...
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1answer
110 views

Advice/literature on combining items with different response scales into composite scales?

Let's say I have some self-report items measured on a 5-point Likert scale (Strongly Disagree to Strongly Agree) and other items measured on a 4-point Likert scale (Never, Rarely, Sometimes, Often). ...
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20 views

Z-scores - return values to rank

Does returning z-scores to a set mean and deviation result in a fair comparison? That is if I had 2 groups: group 1 mean = 76, stdev = 8 group 2 mean = 81, stdev = 11. Then to compare group 1 ...
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1answer
64 views

Proper ordering of outlier removal, standardization, downsampling, etc. in a pre-processing pipeline

I have been using several techniques, sometimes in conjunction with one another, in a pre-processing pipeline prior to using the data for supervised machine learning. I was wondering about the ...
2
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74 views

Which variables should I transform, center, and/or standardize in my data for Principal Component Analysis?

I have multiple datasets that I am attempting to use principal component analysis (PCA) on in order to infer the underlying structure of the data. I'm attempting to predict growth increment of ...
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67 views

Z-score calculation for a single variable with readings in multiple units

I ran into little trouble transforming a set of data I need for analysis. I have been trying to analyze results of a lab test as Z-scores. I have an output field with a reading and unit field. Data ...
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1answer
39 views

standardize two categorical variables into same unit

I have two categorical variables that I want to add: fruit portions = portions of fruit per day (a portion representing a handful): 1= never to 7=5 or more portions, and fruit juice frequency = how ...
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50 views

Interpreting standardized betas with log-transformed dependent variables

I've run a multiple linear regression using standardized Betas and a log-transformed dependent variable; the latter transformation is primarily for better approximating linear regression assumptions ...
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65 views

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 ...
2
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2answers
87 views

Why does correlation come out the same on raw data and z-scored (standardized) data?

I just discovered by mistake that raw data and the same z scored data produces the same correlation. Why is this? Can someone walk me through the logic? ...
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1answer
64 views

Standarizing testing data to mean zero and unit variance on its own or from training data

In standarizing the data for supervised classification, one can do the following: 1) Extract mean and variance for each feature from training, use it to standarize both training and testing data. 2) ...
2
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2answers
177 views

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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26 views

How to scale a variable to a specific mean and standard deviation [duplicate]

This may be a dumb question, and I'm certain I should know this, but let's say I have one variable that has a known metric (e.g., variable A has a mean of .7 and standard deviation of .3). How do I ...
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42 views

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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45 views

Analytical formula for distribution of partial sum of standardized random variable

I would like to know if there is an analytical formula for the distribution of partial sums of standardized random variables. (Of course, if one standardizes a random variable, the sum of all the ...
3
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1answer
277 views

Converting standardized betas back to original variables

I realise this is probably a very simple question but after searching I can't find the answer I am looking for. I have a problem where I need to standardize the variables run the (ridge regression) ...
1
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1answer
80 views

Should I standardize my variables for this particular case of cluster analysis?

I'm trying to cluster a list of records based on a (percentage) frequency distribution of variables which add up to 100%. Like Record1 - VarA(25%) VarB(25%) varC(50%) varD(0%) Record2- VarA(50%) ...
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59 views

Should I de-mean a predictor variable before a dummy interaction

Suppose I have the following time-series linear model where $\beta$ is misspecified: $Y(t+1) = \alpha + \beta X(t) + \sum_{i=1}^{10000}\gamma_i Z_i(T) + \varepsilon$ where all parameters are in ...
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0answers
58 views

What are the pros and cons of standardizing variable in presence of an interaction? [duplicate]

I put this question because while reading the benefits of standardizing explanatory variables or not, I read good but contrasting opinions about standardizing when there are interaction in the model. ...
2
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1answer
63 views

Standardization in SPSS

I have a survey based on a Likert-scale (1-5) with around 20 variables and 140 cases. Since some people only cross from 1 to 3 for all questions (variables) and others cross 1-5, I want to standardize ...
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196 views

Is Cohen's $d$ a better measure of effect-size than a simple mean difference for a meta-analysis?

Cohen's $d$ measures the difference between the mean for the experimental group and the control group divided by standard deviation. The Cohen's $d$ statistic produces something that does not add to ...
2
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0answers
38 views

How to correctly standardize spatial data?

I have measurements of a set of socio-economic variables on italian municipalities; the aim is to run a series of clustering algorithms on them, in order to see if any significant pattern of local ...
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1answer
49 views

Scale a matrix to predefined stddev and mean

Today i stumbled upon an filtering algorithm which as final step it says that it scale the output matrix so it will have the same stddev and mean as the input matrix. Is that possible?
2
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0answers
80 views

Standardizing non-normal data for use in distance-based classifier

I have a dataset containing non-normally distributed variables that I want to feed into a distance-based classifier (e.g. K-means). Is it ok to just subtract the mean and divide by the standard ...
2
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0answers
141 views

Why would SVD be 'unstable' if you don't standardize your data first?

I'm reading an article about Direct Linear Transformation which processes data using SVD, and the data set is standardized so that it has zero mean and unit standard deviation (n.b., some people call ...
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1answer
151 views

How do I transform my data so that it has mean zero and standard deviation one?

Given a series of values, 3.00,5.00,7.00,4.00,7.00,5.00,22.00,4.00,6.00,7.00,9.00,6.00,4.00 I need to 'rescale' the data so they have new values with a mean ...
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22 views

Combining critic scores into single rating

I have a collection of scores from critics for various restaurants. Some restaurants are rated by multiple critics and some by only a single critic. Each critic rates restaurants using different ...
2
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107 views

whether to rescale indicator / binary / dummy predictors for LASSO

For the LASSO (and other model selecting procedures) it is crucial to rescale the predictors. The general recommendation I follow is simply to use a 0 mean, 1 standard deviation normalization for ...
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73 views

cross-validation and standardization

In this thread @whuber gave detailed answer about using training data statistics for standardizing cv dataset. My question is how to standardize hold-out dataset in n-fold cross-validation if some ...