immediate need for help, please!

Hello! Does anyone know what is the meaning of a simple dot on the significance and F box on ANOVA analysis?
And what is the meaning when the regression analysis creates the 'excluded variables' box I attached ?
What i have made wrong ?
I would really appreciate your answer !
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Ambassador to the humans
It means it can't perform the test. Whatever model you fit doesn't leave any degrees of freedom for the residuals so you can't actually perform a test with that particular model.


Less is more. Stay pure. Stay poor.
I would follow-up with, what is your sample size and number of predictors? Also, what does the distribution of the DV look like given it is based on an ordinal scale of integers?


Less is more. Stay pure. Stay poor.
Well it is a pretty stupid exercise - unless it is design to show you what a stupid exercise looks like - there would be merit in that.

You are better off just doing a correlogram!


Active Member
For what it's worth, I remember a theory exam where the professor shared erroneous model output to ask us what was wrong. Turns out it had something to do with a non-invertible X matrix and linearly dependent columns. Maybe it is the same aim here.


Ambassador to the humans
Really guys? There just aren't enough observations to fit the model they specified. Maybe they are trying to fit to already averaged data. Maybe they just literally only have less than ten observations. We don't know. But what we can be sure of is that they can't perform a statistical test on the model they have currently.
thank you for the replies!!
I made some changes.... and now i got the following results. The pearson correlation of regression analysis indicated that the variables (covid tests, shifts, machines etc...) are significant , but the coefficients show something different. Could you ,please, explain this to me?
(the hypothesis is that these variables affect the expenses of the dialysis units)




No cake for spunky
What do you mean by "show something different? Test of significance have nothing at all to do with if the effect size is a certain order of magnitude. They only show if what you find in your sample is likely to exist in the actual population. If the real world effect size (the slope or correlation) is small it is small. Correlations are bad ways to run analysis anyhow because they don't control for other variables. Regression is better.

I am not sure what you mean by pearson correlation when it comes to regression. Regression is not a Pearson correlation. The slope is one that takes into account the impact of other variables in the model. This won't be the same thing that a simple correlation between two variables is in nearly all cases. Pearson makes no sense if your predictors are ordinal or likert in any case or if the results are non-linear.


No cake for spunky
If it matters this is a list of the variables
MODEL Qtr2_Wage=    
"Age 25 to 44"n 
"Associate’s degree"n 
"Bachelor’s degree"n
"Beyond a bachelor’s degree"n
"High school diploma or equivalen"n 
/*"Individuals has a significant di"n */
"Postsecondary education no degre"n 
"Race: Black"n 
"Race: More than one"n
"Special education certicate/comp"n
"Age 19 to 24"n 
"Age 45 to 54"n 
"Age 55 to 59"n
"Age 60+"n
'Age 16 to 18'n 
"Race: Asian"n 
"Race: Hawaiian/Pacific Islander"n 
"Race: White"n
"Foster care youth"n
"Psychosocial and psychological d"n 
"Intellectual and learning disabi"n
"Physical disability"n 
"Auditory and communicative disab"n 
"TANF recipient"n
"Single parent"n 
"Received career services"n
"Received training services"n 
"Received other services"n 
"Received public support at appli"n
"Employed at application"n
"Homeless individual, runaway you"n 
"Limited English-language profici"n
"Migrant and seasonal farmworker"n 
"Long-term unemployed"n 
/*"Individuals is most significant"n */
"Ethnicity-Hispanic Ethnicity"n 
"Displaced homemaker"n
"Construction Employment"n 
"Educational, or Health Care Rela"n 
"Financial Services Employment"n
"Information Services Employment"n
"Leisure, Hospitality, or Enterta"n
"Natural Resources Employment"n 
"Other Services Employment"n 
"Trade and Transportation Employm"n 
"Professional and Business Servic"n 
"Manufacturing Related Employment"n
sewe is the dummy for paid services. You either get one or you don't.