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:
258
Step-by-step explanation:
Set up the two equations needed (x is the adult tickets and y is the student tickets)
x+y=372
6x+2y=1776
Solve by elimination
-2(x+y=372)
=-2x-2y=-744
Cancel like figures:
-2x-2y=-744
6x+2y=1776
= 4x=1032
x=258
Answer:
e
Step-by-step explanation:
e
The area is 11.61 square feet and the perimeter is 14 feet. i hope this helps :)
Area=Length times width
Perimeter=Length+Length+width+width
Answer:
<u>81920</u>
Step-by-step explanation:
Finding the common ratio (r) :
Finding the 14th term :
- a₁₄ = ar¹⁴⁻¹
- a₁₄ = ar¹³
- a₁₄ = (10)(2)¹³
- a₁₄ = (10)(8192)
- a₁₄ = <u>81920</u>
