We can use the 9 inches wide to determine that 18 inches of the 42 inches are the wide sides. 42 - 18 = 24, so we divide 24 by how many long sides there are, 2. 24 ÷ 2 = 12. The box was 12 inches long.
Below are the choices that can be found from other sources:
A. 42
<span>B. 45 </span>
<span>C. 47 </span>
<span>D. 48 </span>
<span>E. 49
</span>
The answer is C or 47. The object’s resultant angle of motion with the +x-axis after the collision is 47. The reason for that is f<span>rom object A’s x-momentum is 5.7 × 104 kilogram meters/second and its y-momentum is 6.2 × 104 kilogram meters/second, we know that tan of the angle from the x-axis is 6.2 / 5.7 = 1.09 and acrtan 1.09 = 47.4</span>
Answer : (13)
Let x be the number of party favors in each (27 boxes)
Let y be the number of favors in last box
Given : total of party favors = 1552
27 boxes + last box = 1552
27x + y = 1552
We divide 1552 by 27, the quotient will be our x and the remainder will be y(number of party favors in last box)
Use long division
= 57 and remainder is 13
the number of party favors in each of (27 boxes) = 57
the number of party favors in last box = 13
So, there are 13 party favors in last box.
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Answer:
Option b (factor) is the correct choice.
Step-by-step explanation:
ANOVA would be used to assess whenever there were other statistically representative variations seen between results of two or even more individual (totally unconnected) categories.
<u>Two different kinds of independent variables exist such as:</u>
If the explanatory variables are such an effective variable otherwise we modify the argument of the variable to test its effect on something like a specific parameter.
Certain solutions don't apply to the specified scenario. So choice B was its perfect method for that.
Answer:
A
Step-by-step explanation:
The linear model can be assessed by the checking the independent variables having power 1 which shows the linear relationship between x and y. For example, as in the option B, C and D, the power of Xi's is one. Whereas the non linear model has the power for independent variables greater than 1. For example, as in option A the model is a quadratic model because X associated with β2 has a power of a 2.
Thus the nonlinear model can be expressed as
Y = β0 + β1X + (β2X)2 + ε.