Answer:
<u>Alejandro went to 8 matinee shows and 4 evening shows.</u>
<u>Our system of equations:</u>
<u>x + y = 12</u>
<u>7x + 12y = 104</u>
Correct statement and question:
Alejandro loves to go to the movies. He goes both at night and during the day. The cost of a matinee is 7 dollars. The cost of an evening show is 12 dollars.
Alejandro went to see a total of 12 movies and spent $ 104. How many of each type of movie did he attend? Write a system of equations.
Source:
Previous question that can be found at brainly
Step-by-step explanation:
Step 1:
Let x to represent the number of matinee shows Alejandro went to.
Let y to represent the number of evening shows Alejandro went to.
Now, let's write our system of equations:
x + y = 12
7x + 12y = 104
*********************
x = 12 - y
*********************
7 (12 - y) + 12y = 104
84 - 7y + 12y = 104
5y = 104 - 84
5y = 20
y = 20/5
<u>y = 4 ⇒ x = 12 - 4 = 8</u>
<u>Alejandro went to 8 matinee shows and 4 evening shows.</u>
Since the 37 is negative the parabola will open downward.
The coefficient on the outside of the ^2 tells you if it opens up or down. If it's positive it opens upward and if it's negative it opens downward.
For the parabola to open sideways it would be a form of x = y^2
Answer:
-24 x^7
Step-by-step explanation:
(-2x^2)^3 ·3x
(-2x^2) (-2x^2) (-2x^2)*3x
-8 x^6 *3x
-24 x^7
Answer:
(a) <em>Linear regression</em> is used to estimate dependent variable which is continuous by using a independent variable set. <em>Logistic regression</em> we predict the dependent variable which is categorical using a set of independent variables.
(b) Finding the relationship between the Number of doors in the house vs the number of openings. Suppose that the number of door is a dependent variable X and the number of openings is an independent variable Y.
Step-by-step explanation:
(a) Linear regression is used to estimate dependent variable which is continuous by using a independent variable set .whereas In the logistic regression we predict the dependent variable which is categorical using a set of independent variables. Linear regression is regression problem solving method while logistic regression is having use for solving the classification problem.
(b) Example: Finding the relationship between the Number of doors in the house vs the number of openings. Suppose that the number of door is a dependent variable X and the number of openings is an independent variable Y.
If I am to predict that increasing or reducing the X will have an effect on the input variable X or by how much we will make a regression to find the variance that define the relationship or strong relationship status between them. I will run the regression on any computing software and check the stats result to measure the relationship and plots.
Answer:
(A) ![A=\left[\begin{array}{ccc}10&20&40\end{array}\right]](https://tex.z-dn.net/?f=A%3D%5Cleft%5B%5Cbegin%7Barray%7D%7Bccc%7D10%2620%2640%5Cend%7Barray%7D%5Cright%5D)
(B) ![B=\left[\begin{array}{ccc}11&22&44\end{array}\right]](https://tex.z-dn.net/?f=B%3D%5Cleft%5B%5Cbegin%7Barray%7D%7Bccc%7D11%2622%2644%5Cend%7Barray%7D%5Cright%5D)
(C) ![A+B=\left[\begin{array}{ccc}21&42&84\end{array}\right]](https://tex.z-dn.net/?f=A%2BB%3D%5Cleft%5B%5Cbegin%7Barray%7D%7Bccc%7D21%2642%2684%5Cend%7Barray%7D%5Cright%5D)
Step-by-step explanation:
The manager ordered 10 lb of tomatoes, 20 lb of zucchini, and 40 lb of onions from a local farmer one week.
(A)
Matrix <em>A</em> represents the amount of each item ordered. It is 1 × 3 matrix.
Then matrix <em>A</em> is:
![A=\left[\begin{array}{ccc}10&20&40\end{array}\right]](https://tex.z-dn.net/?f=A%3D%5Cleft%5B%5Cbegin%7Barray%7D%7Bccc%7D10%2620%2640%5Cend%7Barray%7D%5Cright%5D)
(B)
Next week the manager increases the order of all the products by 10%.
Then the amount of new orders are:
Tomatoes ![=10\times [1+\frac{10}{100}]=10\times1.10=11](https://tex.z-dn.net/?f=%3D10%5Ctimes%20%5B1%2B%5Cfrac%7B10%7D%7B100%7D%5D%3D10%5Ctimes1.10%3D11)
Zucchini ![=20\times [1+\frac{10}{100}]=20\times1.10=22](https://tex.z-dn.net/?f=%3D20%5Ctimes%20%5B1%2B%5Cfrac%7B10%7D%7B100%7D%5D%3D20%5Ctimes1.10%3D22)
Onions ![=40\times [1+\frac{10}{100}]=40\times1.10=44](https://tex.z-dn.net/?f=%3D40%5Ctimes%20%5B1%2B%5Cfrac%7B10%7D%7B100%7D%5D%3D40%5Ctimes1.10%3D44)
Th matrix <em>B</em> represents the amount of each order for the next week. Then matrix <em>B</em> is:
![B=\left[\begin{array}{ccc}11&22&44\end{array}\right]](https://tex.z-dn.net/?f=B%3D%5Cleft%5B%5Cbegin%7Barray%7D%7Bccc%7D11%2622%2644%5Cend%7Barray%7D%5Cright%5D)
(C)
Add the two matrix <em>A</em> and <em>B</em> as follows:
![A+B=\left[\begin{array}{ccc}10&20&40\end{array}\right]+\left[\begin{array}{ccc}11&22&44\end{array}\right]\\=\left[\begin{array}{ccc}(10+11)&(20+22)&(40+44)\end{array}\right]\\=\left[\begin{array}{ccc}21&42&84\end{array}\right]](https://tex.z-dn.net/?f=A%2BB%3D%5Cleft%5B%5Cbegin%7Barray%7D%7Bccc%7D10%2620%2640%5Cend%7Barray%7D%5Cright%5D%2B%5Cleft%5B%5Cbegin%7Barray%7D%7Bccc%7D11%2622%2644%5Cend%7Barray%7D%5Cright%5D%5C%5C%3D%5Cleft%5B%5Cbegin%7Barray%7D%7Bccc%7D%2810%2B11%29%26%2820%2B22%29%26%2840%2B44%29%5Cend%7Barray%7D%5Cright%5D%5C%5C%3D%5Cleft%5B%5Cbegin%7Barray%7D%7Bccc%7D21%2642%2684%5Cend%7Barray%7D%5Cright%5D)
The entries of the matrix (<em>A</em> + <em>B</em>) represent the amount of tomatoes, zucchini and onions ordered for two weeks.