The angle between two vectors is:
CosФ = u - v / Magnitude(u) x magnitude(v)
Magnitude of u = SQRT(7^2 + -2^2) = SQRT(49 +4) = SQRT(53)
Magnitude of v = SQRT(-1^2 +2^2) = SQRT(1 +4) = SQRT(5)
u x v = (7 x -1) + (-2 x 2) = -7 + -4 = -11
cosФ = -11 / sqrt(53) x sqrt(5)
cosФ = -11sqrt265) / 265
Ф =cos^-1(-11sqrt265) / 265)
Ф=132.51 degrees.
Logₐx=b means aᵇ=x
reverse
aᵇ=x means logₐx=b
so
2³=x means log₂x=3
I say it is A
Answer:
B. (b+3c)+(b+3c)
C. 2(b)+2(3c)
Step-by-step explanation:
we have
Distribute the number 2
Verify each case
case A) 3(b+2c)
distribute the number 3
therefore
Choice A is not equivalent to the given expression
case B) (b+3c)+(b+3c)
Combine like terms
therefore
Choice B is equivalent to the given expression
case C) 2(b)+2(3c)
Multiply both terns by 2
therefore
Choice C is equivalent to the given expression
2.57 + 5x = 25.92 is the equation and when you solve for x you would get x = 4.67
Answer:
See below for answers and explanations
Step-by-step explanation:
Your table is a little weird, so I will try my best:
a) A linear regression equation for the line of best fit would be y-hat = 0.018x - 24.5111 where y-hat is the predicted value for the recorded weight gain (in pounds) and x is the additional daily caloric intake. You can put the data into lists and use the LinReg function on the TI-84 to get this equation.
b) It seems that as the pony's additional calorie intake increases, the weight gain also increases in pounds
c) Set x equal to 2300 and solve for y-hat:
y-hat = 0.018x - 24.5111
y-hat = 0.018(2300) - 24.5111
y-hat = 41.4 - 24.5111
y-hat = 16.8889
So our predicted value for the weight gain based on an additional 2300 calorie intake is 16.9 pounds.
