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Juliette [100K]
3 years ago
12

QUESTION: Sarah is dividing 1/4 pound of cashews and 1/2 pound of almonds into 5 plastic bags. What fraction of a pound of nuts

will be in each plastic bag.
SIDE NOTE: I need the answer to be in a fraction and I can simplify it myself to if you don’t want to because I don’t quite care bout the simplification part right now so don’t bother doing that part for me.
Mathematics
1 answer:
Radda [10]3 years ago
6 0

Answer:

The no. of cashews in pounds=1/4

The no.of almonds in pound=1/2

Therefore total no. of cashews in each bag=1/4÷5

Total no.of almonds in each bag=1/2÷5

Cashews in each bag=1/20

Almonds in each bag=1/10

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2(-g+2)

Step-by-step explanation

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point form: (-2,7)

equation form: X = -2, Y = 7

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makkiz [27]

Mistake in Line 2 : Was in the determining the values for a ,b,c

Mistake in Line 4 : Not taking the square roots of both sides.

Step-by-step explanation:

{a}^{2}  +  {b}^{2}  =  {c}^{2}

First Mistake : Line 2

a = x \\ b = 6 \\ c = 10

Second Mistake : Line 4

136 =  {x}^{2}  \\ not \\ 136 = x

Correct Solution :

{x}^{2}  +  {6}^{2}  =  {10}^{2}  \\  {x}^{2}  =  {10}^{2}  -  {6}^{2}  \\  {x}^{2}  = 100 - 36 \\

{x}^{2}  = 64 \\  \sqrt{ {x}^{2} }  =  \sqrt{64}  \\ x = 6

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3 years ago
. The estimate regression equation for a model involving two independent variables and 10 observations follows.y = 29.1270 + 0.5
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Answer:

b) y = 289.815 when x_1 = 180 \text{ and } x_2 = 310

Step-by-step explanation:

We are given the following information in the question:

y = 29.1270 + 0.5906x_1 + 0.4980x_2

where y is the dependent variable,

x_1, x_2 are the independent variable.

The multiple regression equation is of the form:

y = b_0 + b_1x_1 + b_2x_2

where,

b_0: is the intercept of the equation and is the value of dependent variable when all the independent variable are zero.

b_1: It is the slope coefficient of the independent variable x_1.

b_2: It is the slope coefficient of the independent variable x_2.

  • The regression coefficient in multiple regression is the slope of the linear relationship between the dependent and the part of a predictor variable that is independent of all other predictor variables.

Comparing the equations, we get:

b_1 = 0.5906\\b_2 = 0.4980

  • This means holding x_2 constant, a change of one in x_1 is associated with a change of 0.5906 in the dependent variable.
  • This means holding x_1 constant, a change of 1 in x_2 is associated with a change of 0.4980 in the dependent variable.

b) We have to estimate the value of y

y = 29.1270 + 0.5906(180) + 0.4980(310) = 289.815

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Step-by-step explanation:

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