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Ipatiy [6.2K]
3 years ago
10

What is y=2/3x+1 the

Mathematics
1 answer:
iVinArrow [24]3 years ago
8 0

Answer:

Step-by-step explanation:

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Enter a negitive number that has an absolute value greater than 10
Masja [62]

Answer:

|-11 |

Step-by-step explanation:

5 0
3 years ago
For f(x) = 2x + 1 and g(x) = x^2- 7, find (f - g)(x). ?
Irina18 [472]

Answer:

(f-g)(x)=-x^(2)+2x+8

the solutions are:

<em><u>x=4 or x=-2</u></em>

Step-by-step explanation:

(f-g)(x)=2x+1-(x^(2)-7)

(f-g)(x)=-x^(2)+2x+1+7

(f-g)(x)=-x^(2)+2x+8

does this help or should I solve for the zeros/solutions of this quadratic equation?

then:

-x^(2)+2x+8=0

-(x^(2)-2x-8)=0

x^(2)-2x-8=0

(x-4)(x+2)=0

<em><u>x=4 or x=-2</u></em>

4 0
3 years ago
Read 2 more answers
Help me with this question
Flauer [41]

Answer:

5

Step-by-step explanation:

Always multiply the base by the height that is straight, (It is more accurate).

2x5=10 and 10/2=5.

The well known formula for the area of a triangle is BxH divided by 2.

3 0
3 years ago
3. Please answer the following questions: a. What criterion in regression are we trying to minimize when we estimate our regress
Damm [24]

Answer:

Regression : Impact of y on x ; Regression Function : y = a + b(x)

Optimum Least square criteria, with assumptions - linear parameters, homoscedasticity, no autocorrelation, no multicollinearity.

Step-by-step explanation:

Regression is a statistical tool used to calculate the impact of independent/ explanatory variable (x) on dependent variable (y). Eg : Impact of temperature on ice cream sales.

Population regression function is linear function, establishing a hypothetical theoretical relationship between independent variable x & dependent variable y.

Regression Equation is : y = a + b(x)  ;

where : a is the autonomous value of dependent variable y ; b represents the coefficient of change in dependent variable y due to change in independent variable x.

Optimum Least Square method criterion is used while estimating regression model. The criteria minimises the squares of residuals, where residuals are the differences between observed values & estimated values. It is used as a measure of how well the estimated regression line fits the actual data.

Assumptions made while an OLS regression model are : Linear in parameters, Homoscedasticity (variables constant errors), No autocorrelation (errors correlation), No multicollinearity ( independent variables' correlation)

8 0
3 years ago
pencils come in packages of 10. Erasers come in packages of 12. phillip wants to purchase the smallest number of pencils and era
iVinArrow [24]
120 packages of pencils and erasers. 120 is the GCF. 10 × 20 = 120
3 0
3 years ago
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