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:
A. (-7 -2)
Step-by-step explanation:
You can eliminate y by multiplying the first equation by 7 and subtracting 6 times the second equation:
7(-3x +6y) -6(5x +7y) = 7(9) -6(-49)
-21x +42y -30x -42y = 63 +294 . . . . eliminate parentheses
-51x = 357 . . . . . . . . collect terms
x = -7 . . . . . . . divide by -51. This matches answer choice A.
The $1.25 one for 9 Oz box of rice would be the best buy.
<h3>How to find the Unit Price?</h3>
To get the best buy among the given items and prices, we need to find the unit price. Thus, the formula is;
Unit price = Price/Quantity
A) Unit Price = 0.90/6 = 0.15
B) Unit Price = 1.93/12 = 0.15083
C) Unit price = 2.42/16
Unit Price = 0.15125
D) Unit Price = 1.25/9 = 0.138
The $1.25 one for 9 Oz box of rice would be the best buy.
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Answer:
7
Step-by-step explanation:
Answer:
Each shelf holds 30 inches of filling.
Step-by-step explanation:
Divide 180 inches of filling by the six shelves and you get 30 inches of filling per shelf
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