The assumptions of a regression model can be evaluated by plotting and analyzing the error terms.
Important assumptions in regression model analysis are
- There should be a linear and additive relationship between dependent (response) variable and independent (predictor) variable(s).
- There should be no correlation between the residual (error) terms. Absence of this phenomenon is known as auto correlation.
- The independent variables should not be correlated. Absence of this phenomenon is known as multi col-linearity.
- The error terms must have constant variance. This phenomenon is known as homoskedasticity. The presence of non-constant variance is referred to heteroskedasticity.
- The error terms must be normally distributed.
Hence we can conclude that the assumptions of a regression model can be evaluated by plotting and analyzing the error terms.
Learn more about regression model here
brainly.com/question/15408346
#SPJ4
Answer:
I NEED MORE DETAILS
Step-by-step explanation:
ITS ALSO BLURRY
The pattern is increasing by 10 then a ding 1 to the next number. Hope this helps! :)
Answer:
5 1/4 times 1/2 = 2.625. as a fraction 2.625 is 2 5/8 because .625 could be drawn out to 625/1000 125 goes into 625 and 1,000 625 divided by 125 = 5 and 1,000 divided by 125 is 8 we already had 2 so 2 5/8
Step-by-step explanation:
Answer:
5.95
Step-by-step explanation:
that is because 96 is rounded too 100
so its 5.9500 = 5.95
