Linked Questions

5
votes
1answer
4k views

Need help understanding what a natural log transformation is actually doing and why specific transformations are required for linear regression [duplicate]

I’m taking an online “Intro to AI” course for which I’m doing some azure machine learning labs. This course is largely about how to apply azure ML solutions and, while there is an “essential math for ...
3
votes
3answers
773 views

Why it is good to take log on Finance data? Does it have nice properties? [duplicate]

Just like what I am asking in the title. I see nearly all the financial datas take logs before the data analysing step, Why? Dose it have nice properties?
1
vote
1answer
2k views

For my study design: When to log-transform data vs. when to use a non-parametric approach [duplicate]

Edit Purpose of my study I have weather stations collecting data inside and outside low-tech greenhouses. Four of the weather stations are inside, and one is outside. They are collecting temperature, ...
1
vote
3answers
160 views

Why is it okay to take the log (or any other transformation) of the dependent variable? [duplicate]

Why is it common practice to take the log of the dependent variable Y? To be clear, I understand that under appropriate circumstances that taking the log can help normalize the distribution/linearize ...
1
vote
0answers
57 views

Why would you want to use a transformation function? [duplicate]

I am trying to understand the benefits of transformation functions. Mainly, I am trying to understand the kick / the motivation to even attempt a transformation function on a sample data being ...
194
votes
8answers
411k views

In linear regression, when is it appropriate to use the log of an independent variable instead of the actual values?

Am I looking for a better behaved distribution for the independent variable in question, or to reduce the effect of outliers, or something else?
52
votes
3answers
62k views

Interpretation of log transformed predictor and/or response

I'm wondering if it makes a difference in interpretation whether only the dependent, both the dependent and independent, or only the independent variables are log transformed. Consider the case of <...
18
votes
5answers
50k views

What could be the reason for using square root transformation on data?

What is the primary reason that someone would apply the square root transformation to their data? I always observe that doing this always increases the $R^2$. However, this is probably just due to ...
22
votes
2answers
28k views

Transforming proportion data: when arcsin square root is not enough

Is there a (stronger?) alternative to the arcsin square root transformation for percentage/proportion data? In the data set I'm working on at the moment, marked heteroscedasticity remains after I ...
15
votes
4answers
4k views

Is Prophet from Facebook any different from a linear regression?

So what I've read about Facebook's prophet is that it basically breaks down the time series into trend and seasonality. For example, an additive model would be written as: $$ y(t) = g(t) + s(t) + h(t)...
10
votes
4answers
20k views

How to interpret logarithmically transformed coefficients in linear regression?

My situation is: I have 1 continuous dependent and 1 continuous predictor variable that I've logarithmically transformed to normalise their residuals for simple linear regression. I would ...
13
votes
4answers
18k views

Statsmodels says ARIMA is not appropriate because series is not stationary, how is it testing that?

I have a time series that I am trying to model with Python's statsmodels ARIMA api. When I apply the following: ...
12
votes
2answers
1k views

Are normally distributed X and Y more likely to result in normally distributed residuals?

Here the misinterpretation of the assumption of normality in linear regression is discussed (that the 'normality' refers the the X and/or Y rather than the residuals), and the poster asks if it is ...
4
votes
3answers
2k views

Interpreting autocorrelation in time series residuals

I am trying to fit an ARIMA model to the following data minus the last 12 datapoints: http://users.stat.umn.edu/~kb/classes/5932/data/beer.txt The first thing I did was take the log-difference to get ...
7
votes
2answers
13k views

Choosing Between Additive and Multiplicative Model?

I have a set of data that I am currently analysing. I am having difficulty in deciding whether an Additive model should be used to forecast the data, or if I should use a Multiplicative model. I ...

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