56% chance it won’t be a dime
Answer:
14
Step-by-step explanation:
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 rule used to describe this transformation is (x, y)→(x - 4, y + 5)
<h3>
Transformation</h3>
Transformation is the movement of a point from its initial location to a new location. Types of transformation are<em> rotation, reflection, translation and dilation.</em>
If a point A(x, y) is translated a units left and b units up. the new point is at A'(x - a, y + b)
Given Trapezoid WKRP was translated 4 units to the left and 5 units up on a coordinate grid to create trapezoid W’K’R’P’. The rule is given by:
(x, y)→(x - 4, y + 5)
The rule used to describe this transformation is (x, y)→(x - 4, y + 5)
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Answer:
7.75
Step-by-step explanation:
