# Linked Questions

8answers
63k views

### When forcing intercept of 0 in linear regression is acceptable/advisable [duplicate]

I have a regression model to estimate the completion time of a process, based on various factors. I have 200 trials of these processes, where the 9 factors being measured vary widely. When I perform a ...
2answers
8k views

### Deliberately fitting a model without intercept [duplicate]

Is there a situation in which the mean of a Y variable is not 0 (e.g. not standardized), but we would still fit a regression model without intercept? It would yield a worse fitting model, so is there ...
2answers
44k views

### Significance of Regression Intercept (R lm model) [duplicate]

Question: Having performanced a linear regression in R with the lm function, I'm not sure how to interpret the results for the Intercept (as shown below). It seems the probability of the intercept'...
3answers
3k views

### What are the uses and pitfalls of regression through the origin? [duplicate]

Spuriously high R-squared is one of the pitfalls of regression through the origin (i.e. zero-intercept models). If the predictors do not contain zeroes, then is it an extrapolation? What are the uses ...
1answer
4k views

### Ridge Regression: When should the intercept be included ? What is the purpose of the intercept term? [duplicate]

I am trying to determine what is the purpose of including the intercept term in ridge regression. In what situations should I include the intercept term ? And in what situations should I not ...
1answer
3k views

### Constant in OLS model [duplicate]

Sometimes in OLS model we have constant for example -2345 significant and doesn't have a mean. Why we must keep it in the model? Why when we drop it the results change? What does it mean? And ...
0answers
4k views

### To exclude or include the intercept in GLM model [duplicate]

When is is appropropriate to include or exclude the intercept from a regression model? SPSS provides this option in the GLM menu. I am assessing group difference (gender) on tasks performed (X) and ...
1answer
2k views

### Regression: Insignificant Intercept [duplicate]

I ran a regression and the intercept is statistically insignificant (the p-value is greater than 0.05). I tried to look in some textbooks as to how to handle this scenario but I am still unsure. One ...
0answers
2k views

### Explain the fit_intercept parameter in some scikit learn classifiers [duplicate]

I'm fairly new to machine learning and I am using the Linear SVM classifier to classify some text data and I was wondering what exactly does the fit_intercept parameter does and what would be a good ...
1answer
1k views

### OLS with categorical variables [duplicate]

1) When we omit the intercept, aren't we forcing the regression line through the origin? Does that pose any problem because we assume that there is no variable that affects the outcome other than the ...
1answer
212 views

### why is constant important in machine learning - linear regression? [duplicate]

I have been reading about linear regression a lot on internet. And people everywhere use a model: y = w*x+b and I have huge difficulties to understand why? As well ...
0answers
531 views

### Logical reasons for choosing regression through the origin [duplicate]

Is it reasonable to choose a regression model with a value of 0 for the intercept when this makes logical sense? For example, I am trying to model a physical ...
1answer
446 views

### Can I leave intercept out in OLS? [duplicate]

I have a model similar to the following: y = a + b + c + d + e; a,b, and ...
0answers
335 views

### Regression Through Origin [duplicate]

I was reading about (simple) linear regression through origin and I have the following questions: What are the standard assumptions of such a regression model? I am asking this of the true model not ...
1answer
135 views

### Linear Regression - with or without intercept [duplicate]

Difference between linear regression with or without intercept? Why and when to use which one?

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