Linked Questions

3
votes
0answers
464 views

Interpreting the residuals vs. fitted values plot [duplicate]

Residuals vs. Fitted Values plot Can someone tell me which OLS assumptions might be violated according to the figure and why? Moreover, what are the consequences for the point estimators and the ...
0
votes
0answers
38 views

Cannot understand this residuals plot in r [duplicate]

I am very new to r and statistics in general. I am trying to test for homogeneity of variance on a multiple linear regression model I have created, and as I understand this is done by checking ...
85
votes
1answer
72k views

Interpreting plot.lm()

I had a question about interpreting the graphs generated by plot(lm) in R. I was wondering if you guys could tell me how to interpret the scale-location and leverage-residual plots? Any comments ...
26
votes
2answers
37k views

Interpretation of plot (glm.model)

Can anyone tell me how to interpret the 'residuals vs fitted', 'normal q-q', 'scale-location', and 'residuals vs leverage' plots? I am fitting a binomial GLM, saving it and then plotting it.
19
votes
2answers
6k views

Is there i.i.d. assumption on logistic regression?

Is there i.i.d. assumption on the response variable of logistic regression? For example, suppose we have $1000$ data points. It seems the response $Y_i$ is coming from a Bernoulli distribution with $...
6
votes
4answers
7k views

Trying to understand the fitted vs residual plot? [duplicate]

A good residual vs fitted plot has three characteristics: The residuals "bounce randomly" around the 0 line. This suggests that the assumption that the relationship is linear is reasonable. The ...
3
votes
3answers
10k views

How to test for independence of residuals in linear model?

How to test for independence of residuals in linear model? What can I plot? What can I look for in the plots? Or are there some other statistics that I can compute?
-2
votes
1answer
2k views

What does this scatterplot mean? Uniform distributions? [closed]

I am very new to statistics and prob theory: I am looking at a scatter plot of two random variables, both uniformly distributed on $(0,1)$. The plot is approximatively a straight line, and the book ...
1
vote
1answer
1k views

What does the residuals vs fitted regression line express?

So what can I infer from this red regression line? What does it mean for the regression line to get positive residual values or negative residual values? I know e.g. that I can infer that the more ...
1
vote
1answer
1k views

help for interpreting the residuals vs. fitted values plot

I have an ordinal variable (scale of stress) considered as continuous predictor in a multivariate linear regression. I would like to verify the assumption of linearity and this is my residuals vs. ...
4
votes
1answer
1k views

Interpreting linear regression residual plots using R

I'm investigating whether there is a relationship between the day of the week and an outcome value using linear regression in R, and would like to understand how to ...
1
vote
2answers
545 views

Does this plot suggest violation of equal variance?

My model has 1 continuous outcome. Above is the residuals vs. fitted values plot. I know that if the equal variance assumption holds, then the residuals should be scattered evenly around 0 line with ...
3
votes
1answer
439 views

Tilted rectangle in residuals vs fitted plot

When performing diagnostics on an OLS model, what can make a plot of the predicted responses vs the residuals. Ideally we want a horizontal rectangle shape. But what does it mean when the plot is a ...
1
vote
2answers
254 views

Model has a Great Fit, Significant Variables but Residuals are Not Normally Distributed. How should we proceed?

I have a data on some overall conversion rates (i.e. out of x users visiting, y buy something hence y/x is my conversion rate, essentially proportions) over a time period, now this overall proportion ...
1
vote
1answer
311 views

Heteroskedasticity: graphical visualization

Often it is said that heteroskedasticty could be assessed in a graphical way: for instance it can be inferred by looking at the residuals of a regression. However, this seems to me quite discretionary....

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