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### What is the difference between lm(log(y) ~ x) and glm(y ~ x, family = gaussian(link = “log”))? [duplicate]

Is all in the title. I would like to know if there is any difference in terms of coefficients, residuals, p-values, but also conceptually.
166k views

### What is the difference between linear regression on y with x and x with y?

The Pearson correlation coefficient of x and y is the same, whether you compute pearson(x, y) or pearson(y, x). This suggests that doing a linear regression of y given x or x given y should be the ...
34k views

### What is a complete list of the usual assumptions for linear regression?

What are the usual assumptions for linear regression? Do they include: a linear relationship between the independent and dependent variable independent errors normal distribution of errors ...
69k views

### Transforming variables for multiple regression in R

I am trying to perform a multiple regression in R. However, my dependent variable has the following plot: Here is a scatterplot matrix with all my variables (...
3k views

### What regression model is the most appropriate to use with count data?

I am trying to get a little into statistics, but I am stuck with something. My data are as follows: ...
185 views

### Obtaining an estimator for z given an estimator for log z

As per gung's advice in Getting the equation from R's lm when using a product, I am starting a new thread for this question. I have a model $\widehat{\log z} = a + bx + cy + dxy$ for random ...
115 views

### Notation: Is the model linear or loglinear? $E(\ln Y|X)=X\beta$

I'm given a model of the form $E(\ln Y|X)=X\beta$. Should I call it a linear model or loglinear model? I'm assuming $Y$ is log-normally distributed.
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### What model to use if factors are assumed to have a multiplicative effect on the dependent variable?

In the general linear model we assume that different factors have an additive effect on the measured numerical target. For example, in the model we can see that being a male adds, on average, 20 kg to ...