# Questions tagged [data-transformation]

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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### Transforming extremely skewed distributions

Assume that I have a variable whose distribution is skewed positively to a very high degree, such that taking the log will not be sufficient in order to bring it within the range of skewness for a ...
25k views

### Linear model Heteroscedasticity

I have the following linear model: To address the residuals heteroscedasticity I have tried to apply a log transformation on the dependent variable as $\log(Y + 1)$ but I still see the same fan out ...
5k views

### Express answers in terms of original units, in Box-Cox transformed data

For some measurements, the results of an analysis are appropriately presented on the transformed scale. In most of the cases, however, it's desirable to present the results on the original scale of ...
6k views

### Empirical logit transformation on percentage data

I have already used the logit transform on my outcome variables (which are displayed in percentages). However, this obviously gives me -INF values and since my data includes a lot of zeros in some ...
5k views

### Interpretation of log(1 + x) transformed predictor

Interpretation of log transformed predictor neatly explains how to interpret a log transformed predictor in OLS. Does the interpretation change if there are 0s in ...
16k views

### How to log transform data with a large number of zeros

I have a dataset comprised of continuous values that have about 30-50% zeros and a large range (10^3 - 10^10). I believe these zeros are not a result of missing data and are the result of the ...
11k views

### making predictions with log-log regression model

Is it necessary to exponentiate the predicted values in a log-log regression model? For example my model is: $\log(y) = \log(x)$ $\log(y) = -0.5141 + 0.5377 \log(x)$ if I wanted to make a ...
9k views

### Best way to optimize MAPE

The MAPE is a metric that can be used for regression problems : $$\mbox{MAPE} = \frac{1}{n}\sum_{t=1}^n \left|\frac{A_t-F_t}{A_t}\right|$$ Where $A$ represents the actual value and $F$ the the ...
10k views

### Why use differencing and Box-Cox in time series?

Why use Differencing and Box-Cox transformation in a time series? From what I read the usefulness of the procedures are Differencing: Making a time series stationary and stabilize the mean Box-Cox: ...
3k views

### How can I estimate theta for the inverse hyperbolic sine transformation?

I would like help with R code to estimate theta for the Inverse Hyperbolic Sine Transformation. This transformation is useful to transform skewed data that contain negative values or zeros. There ...
11k views

### Interpreting Log-Transformed Percentages in OLS

In a log-log model, such as $\log(y) = b_0 + b_1 \log(x)$, I know that with OLS the standard interpretation is a "1% increase in x is associated with a $b_1$% increase in y." I have three related ...
2k views

### Why are log probabilities useful?

Probabilities of a random variable's observations are in the range $[0,1]$, whereas log probabilities transform them to the log scale. What then is the corresponding range of log probabilities, i.e. ...