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.
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Answer:
12.4=12 hours and 24 minutes
Step-by-step explanation:
The answer is A because the square root function needs to be greater than or equal to zero bc the circle is filled and you can’t have a negative radical. It’s also choice A because the -1 is outside of the radical which means it’s being translated downwards from the parent function. Hope that helps ;-;
Answer:
Step-by-step explanation:
y= -(1/2)x - 5
Answer:
Step-by-step explanation:
Below the sea level should be mentioned by negative value
So, It is = - 4.5
