Answer:
answer that do not poru branly
Step-by-step explanation:
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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
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Answer:
She has to read 2/6 more by the end of her vacation if she wants to finish 3/6 (1/2) of the book.
Step-by-step explanation:
If this wasn't the answer you were looking for please tell me so I can redo it.
Answer:
370.28
Step-by-step explanation:
you add the two whole numbers then you add the two fractions and make them a decimal after that put it all together and u get the answer
