Choose all that apply when describing R2. (Hint: 5 options are correct) (Select all that apply.) Can be inflated by adding more variables. Only describes the relationship between quantitative variables. Is used to determine the fit of a model. Is only used in multiple linear regression. Represents the percent of variability in y that can be explained by the model. Can be inflated by removing variables. Referred to as the coefficient of determination or coefficient of multiple determination. In simple linear regression, it is equal to the correlation coefficient r2.

5x + 3y = - 4

step-by-step explanation:

the equation of a line in standard form is

ax + by = c ( a is a positive integer and b, c are integers )

express the line first of all in slope- intercept form

y = mx + c ( m is the slope and c the y-intercept )

to calculate m use the gradient formula

m = ( y₂ - y₁ ) / ( x₂ - x₁ )

with (x₁, y₁ ) = (7, - 3) and (x₂, y₂ ) = (4, - 8)

m = = -

y = - x + c ← is the partial equation

to find c substitute either of the 2 points into the partial equation

using (4, - 8 ), then

- 8 = - + c ⇒ c = -

y = - x - ← in slope-intercept form

multiply all terms by 3 to eliminate the fractions

3y = - 5x - 4 ( add 5x to both sides )

5x + 3y = - 4 ← in standard form

actually your concept is wrong

step-by-step explanation:

150% of x =300

150x=300×100

x=(300×100)÷150

x=200

110698.56 square miles

step-by-step explanation:

multiply 3.8 by 102

387.6

multiply 2.8 by 102

285.6

multiply those two to get