Step-by-step explanation:
Make a table to find the values of x
P.s pick random y value
When x is 1,
y is 4........ Plug 1 into the equation ur given u get the value of y. So, 2(1)+2
When x is 2,
y is 6......... Plug 2 into the equation ur given u get the value of y. So, 2(2)+2
So this point is (2,6)
When x is 3
y is 8 ......2(3)+2
So this point is (3,8)
When x is 4
y is 10.... 2(10)+2
So this point is (4,10)
Hope this helps
Answer: f(x) and g(x) are inverses of each other
<u>Step-by-step explanation:</u>
To find the inverse of a function, swap the x's and y's and then solve for "y"
f(x) = 5x + 2
y = 5x + 2
Swap:
x = 5y + 2
<u> -2 </u> <u> - 2 </u>
x - 2 = 5y
<u>÷5 </u> <u>÷5 </u>
****************************************************************
Hi there! :)
Answer:
Given line with an equation of y = 4x + 3
Parallel lines contain equivalent slopes, so a parallel line to the given equation would contain a slope of m = 4.
Plug in the coordinates of the point given, along with the slope into the equation y = mx + b where:
m = slope
y = y-coordinate of point
x = x-coordinate of point
Solve for the 'b' value, or y-intercept:
y = mx + b
6 = 4(2) + b
6 = 8 + b
b = -2
Rewrite the equation as slope-intercept form:
y = 4x - 2
Answer:
Check the explanation
Step-by-step explanation:
The multiple coefficient of determination, denoted R2, is the ratio of the sum of squares due to regression to the total sum of squares.
The R2 for the new regression is 63209/121222=0.52 (A), indicating that the new estimated multiple regression equation explains 52% (B) of the variability of digital camera sales.
The sum of squares due to error divided by the total sum of squares is 58013/121222=0.4785=0.48 (B), and 1 minus this ratio is 1-0.48=0.52 (B).
The adjusted multiple coefficient of determination, denoted by R2a, for the new regression is 1-[(1-r^2)(n-1/n-k-1)]=0.45 (C).
The mean square due to error divided by the total mean square is 2072/3788=0.5469=0.55 (A) , and 1 minus this ratio is 1-0.55=0.45 (C).
In general, adding independent variables to a multiple regression model reduces the sum of squares due to error (C). The multiple coefficient of determination increases (C), and the adjusted multiple coefficient of determination could either increase or decrease (C).
Adding the independent variable x4 to the multiple regression model increases (B) the multiple coefficient of determination and increases (A) the adjusted multiple coefficient of determination.
Answer:
Step-by-step explanation:
2x^3y and 2yx are not like terms since x^3 can't be added to x since it's not x^3 but x^2.
