Linked Questions

2
votes
1answer
984 views

Labelled Points in plot of lm.fit [duplicate]

The image shown below is the output for plot(lm.fit) on the Boston dataset, where lm.fit=lm(medv~lstat) . Why are some of the ...
0
votes
1answer
55 views

Interpret the multi linear regression graph [duplicate]

Residual fitted normal Q scale location residual leverage graph. Not able to interpret what it means.
0
votes
0answers
65 views

What does this graphs mean in linear regression? [duplicate]

I don't know how to interpret these graphs. Is model well fitted? And how to analyze Cook's dist Vs Leverage plot? I would be very grateful for help. Linear regresssion model shows dependence ...
0
votes
0answers
50 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 ...
0
votes
0answers
44 views

Do these plots imply a good fit of a linear model with normal errors? [duplicate]

Edit: the most obvious way forward would be to convert the data to a linear form. The data below seem to be a polynomial of order five. My question is do we know of any way to convert a polynomial of ...
2
votes
0answers
43 views

Interpretation of four plots returned by lm in R [duplicate]

Below are the residuals plot of a linear model in R. For me, the top left plot is to see if the homoskedasticity hypothesis is verified. The QQ-plot in the top-right location is to check if the ...
0
votes
0answers
32 views

multiple regression model - interpreting graphs for the fit [duplicate]

I have the following r code. I created a multiple linear regression model on a math_and_alcohol dataset. I can see in the summary of the model that the r-squared is .8279 which means the model ...
0
votes
0answers
13 views

Assumption Of Linear Regression [duplicate]

In the graphs below, The only assumption which seems off pretty much clearly is the normal distribution. Although the top left residual plot shows that it is homoscedastic but the top right one has a ...
-2
votes
0answers
12 views

Diagnostic Plot Doubts [duplicate]

These are certain regression plots where I am finding difficulty to diagnose the assumptions of regression which are off. I am pretty much sure that it doesn't have a normal distribution from q-q plot....
0
votes
0answers
7 views

can anyone help with interpreting these multiple linear model assumptions? (r) [duplicate]

i ran some assumptions checks for my multiple linear regression model, but i am having trouble with interpreting the different graphs. i was wondering if anyone could offer some guidance on what they ...
203
votes
4answers
347k views

How to interpret a QQ plot

I am working with a small dataset (21 observations) and have the following normal QQ plot in R: Seeing that the plot does not support normality, what could I infer about the underlying distribution? ...
127
votes
9answers
232k 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 ...
56
votes
2answers
122k views

What does having “constant variance” in a linear regression model mean?

What does having "constant variance" in the error term mean? As I see it, we have a data with one dependent variable and one independent variable. Constant variance is one of the assumptions of linear ...
35
votes
2answers
54k 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.
44
votes
2answers
60k views

PP-plots vs. QQ-plots

What is the difference between probability plots, PP-plots and QQ-plots when trying to analyse a fitted distribution to data?

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