x <- c(5.6, 6.3, 7, 7.7, 8.4)
y <- c(8.8, 12.4, 14.8, 18.2, 20.8)
lin_reg = lm(y ~ x)
summary(lin_reg)
##
## Call:
## lm(formula = y ~ x)
##
## Residuals:
## 1 2 3 4 5
## -0.24 0.38 -0.20 0.22 -0.16
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -14.8000 1.0365 -14.28 0.000744 ***
## x 4.2571 0.1466 29.04 8.97e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3246 on 3 degrees of freedom
## Multiple R-squared: 0.9965, Adjusted R-squared: 0.9953
## F-statistic: 843.1 on 1 and 3 DF, p-value: 8.971e-05
plot(x, y)
abline(lin_reg)
Equation of the regression line:
\[B_0 = -14.800 \\ B_1 = 4.257 \\ y = B_0 + B_1x \\ y = -14.800 + 4.2571x\]
Find the partial derivatives of f:
\[f_x(x, y) = 24 + 6y^2 ; \\ f_y(x,y) = -12x - 24y^2\]
Set each equal to 0 and solve for x and y:
\[f_x(x, y) = 0 => y = +-2 ; \\ f_y(x,y) = 0 => x = -+4\]
Therefore, we have two critical points: (-2, 4), (2, -4). To determine if it corresponds to a relative maximum, minimum, or saddle point, we will look at the second partial derivative of f.
Let z = f(x, y) be differentiable on an open set containing P = (x_0 , y_0), and let
\[D = f_{xx}(x_0, y_0)f_{yy}(x_0, y_0) − f_{xy}^2(x_0, y_0)\]
If D < 0 and \[f_{xx}(x_0,y_0) > 0\], then P is a relative minimum of f
If D > 0 and \[f_{xx}(x_0,y_0) < 0\], then P is a relative maximum of f
If D<0, then P is a saddle point of f
If D = 0, the test is inconclusive
\[f_{xx} = 24 \\ f_{yy} = 48y \\ f_{xy} = 12y\]
For (-2, 4):
\[f_{xx} = 24 \\ f_{yy} = 192 \\ f_{xy} = 48\]
Therefore, \[D(x,y) = 4560\] and (-4, 2) is a relative maximum of f.
For (2, -4):
\[f_{xx} = 24 \\ f_{yy} = -192 \\ f_{xy} = -48\]
Therefore, \[D(x,y) = -4560\] and (-4, 2) is a relative minimum of f.
Step 1. Find the revenue function R ( x, y ).
Revenue for House brand: \[R(x)=x∗(81−21x+17y)\]
Revenue for name brand: \[R(y)=y∗(40+11x−23y)\]
Total Revenue: \[R(x,y)=x∗(81−21x+17y)+y∗(40+11x−23y)\]
\[R(x,y)=81x−21x^2+17xy+40y+11xy−23y^2\]
\[R(x,y)= - 21x^2 - 23y^2 + 28xy + 81x + 40y \]
Step 2. What is the revenue if she sells the “house” brand for $2.30 and the “name” brand for $4.10?
\[R(2.3,4.1)= - 21x^2 - 23y^2 + 28xy + 81x + 40y\]
revenue <- function(x, y){
r = (-21 * x * x) + (-23 * y * y) + (28 * x * y) + (81 * x) + (40 * y)
return (r)}
revenue(2.3, 4.1)
## [1] 116.62
\[C(x,y)= C(96-y, y) = \dfrac{1}{6}x^2 + \dfrac{1}{6}y^2 +7x+25y+700\]
\[ = \dfrac{1}{6}(96-y)^2 + \dfrac{1}{6}y^2 +7(96-y)+25y+700\]
\[ = \dfrac{1}{6}(y^2-192y+9216) + \dfrac{1}{6}y^2 +672 -7y+25y+700\]
\[ = \dfrac{1}{6}y^2-32+1536 + \dfrac{1}{6}y^2 +672 -7y+25y+700\]
\[ C(x,y) = \dfrac{1}{3}y^2-14y + 2908\]
\[ C'(x,y) = \dfrac{2}{3}y-14\]
At C’ = 0; y = 21, x = 96 - y = 75
\[\int\int_R (e^{8x+3y})dA; \ R: 2≤x≤4 \ and \ 2≤y≤4\]
Write your answer in exact form without decimals.
\[\int_2^4\int_2^4 (e^{8x} + e^{3y})dxdy\]
\[\int_2^4 e^{8x}dx * \int_2^4 e^{3y}dy\]
\[\dfrac{1}{8}e^{8x}dx|_2^4 * \dfrac{1}{3}e^{3y}dy|_2^4\]
\[\dfrac{1}{24}e^{8x}|_2^4 * e^{3y}|_2^4\]
\[\dfrac{1}{24}(e^{32}-e^{16})(e^{12}-e^6)\]
1/24*((exp(32)+exp(16))*(exp(12)-exp(6)))
## [1] 5.341561e+17