Linked Questions

-2 votes
1 answer
6k views

How to perform boxcox transformation on data in R tool [duplicate]

Possible Duplicate: How should I transform non-negative data including zeros? Error in boxcox.default(y ~ x) : response variable must be positive I want to perform box cox transformation on ...
Komal's user avatar
  • 61
2 votes
0 answers
5k views

Log transform with 'zero' values [duplicate]

I am doing some explorative work on two large datasets. One from 2001 and one from 2018. The dataset consists of measured soil-parameters and it contains lots of zero's. From the transformations ...
Stevestingray's user avatar
1 vote
0 answers
2k views

How to handle data which contains 0 in a log transformation regression using R tool [duplicate]

Possible Duplicate: How should I transform non-negative data including zeros? I want to perform log transformation regression in R tool but the problem is that I don't know how to handle ...
Komal's user avatar
  • 61
0 votes
1 answer
605 views

How to preserve points near zero when taking logs? [duplicate]

Possible Duplicate: How should I transform non-negative data including zeros? I have a question: Suppose we have a data point $(0,10)$. We then convert to a log scale. Excel gets rid of this ...
Rhubarb Joker's user avatar
1 vote
0 answers
210 views

Data-transformation of data with some values = 0 [duplicate]

Possible Duplicate: How should I transform non-negative data including zeros? I want to log-transform some of my data because the Levene's homogeneity of variances test rejected the null ...
stragu's user avatar
  • 439
1 vote
0 answers
157 views

What is the best mathematical transformation for a variable with many zero values? [duplicate]

Possible Duplicate: How should I transform non-negative data including zeros? I have a continuous variable that has many zeros values and is NOT normal, so I can't use parametric statistics on it....
GEA's user avatar
  • 19
0 votes
0 answers
59 views

Natural logarithm transfomation and zeroes [duplicate]

I am using Stata 13 to estimate a simple regression. Given a rather positive skew of a few of my covariates, I figured to ln-transform the variables. However, I have a substantial amount of zeroes in ...
Rachel's user avatar
  • 247
0 votes
0 answers
51 views

Log transform dependent variable [duplicate]

I have a continuous dependent variable which has a somewhat skewed distribution and hence I want to apply a log transform to it. But the problem is that the target variable can have negative values. ...
Clock Slave's user avatar
  • 1,087
0 votes
0 answers
48 views

How to adjust for a continious variable when the value 0 is distinctly different from the others? [duplicate]

Lets say I want to regress a variable on a covariate which has distinct value zero but the all other values are following some smooth function? It could be e.g. Years of beeing a mom (once you are a ...
PeterStrom's user avatar
0 votes
0 answers
26 views

Appropriate to replace -inf with 0 after log transform? [duplicate]

I have a dataset of customers and their purchase data. Meaning, for each customer id, I have variables indicating number of unique products they bought, Number of online orders they placed, How many ...
The Great's user avatar
  • 3,302
77 votes
5 answers
32k views

How small a quantity should be added to x to avoid taking the log of zero?

I have analysed my data as they are. Now I want to look at my analyses after taking the log of all variables. Many variables contain many zeros. Therefore I add a small quantity to avoid taking the ...
miura's user avatar
  • 3,744
47 votes
8 answers
11k views

Rigorous definition of an outlier?

People often talk about dealing with outliers in statistics. The thing that bothers me about this is that, as far as I can tell, the definition of an outlier is completely subjective. For example, ...
dsimcha's user avatar
  • 8,809
53 votes
1 answer
44k views

Regression: Transforming Variables

When transforming variables, do you have to use all of the same transformation? For example, can I pick and choose differently transformed variables, as in: Let, $x_1,x_2,x_3$ be age, length of ...
Brandon Bertelsen's user avatar
13 votes
5 answers
16k views

What other normalizing transformations are commonly used beyond the common ones like square root, log, etc.?

In the analysis of test scores (e.g., in Education or Psychology), common analysis techniques often assume that data are normally distributed. However, perhaps more often than not, scores tend to ...
Mike Wong's user avatar
  • 437
13 votes
3 answers
32k views

How should you handle cell values equal to zero in a contingency table?

How should you deal with a cell value in a contingency table that is equal to zero in statistical calculations? (Note that such a value can be structural, i.e., it must be zero by definition, or ...
DrWho's user avatar
  • 949

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