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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The expression equivalent to 0.2x is 0.1x
Mr. Kyle will be expected to pay $8,100.
The total cost for his land would be 120 x 90 = 10,800.
Since the city is paying 25%, he must pay the other 75%.
0.75 x 10800 = 8100
A & D are the correct answers!
Answer:
$23.75
Step-by-step explanation:
divide $28.50 by 6 to find the price for 1 bag which is $4.75 then multiply $4.75 by 5 and that equals $23.75
