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3 years ago

100 POINTS!!! Plz Help

2 answers:

8 0

geometric probability are probability Q related to geometric figures. Example: a game in county fair - u throw a bean bag onto a square board w/ 1 big blue circle n 1 smaller red circle inside the blue circle. u win a small prize if bean bag lands in blue and a big prize if its in red.

assume bean bag always lands on the board, the probablity of winning a small prize=P(bean lands in blue)

=(Area of blue circle - Area of red circle)/Area of square

Murljashka [212]3 years ago

8 0

During a football game, someone drops a ball from a blimp above. it lands within the playing field which is rectangular in shape with 100 yards in middle and 10 yards for end zone at each end.

Prob(ball land in end zone) = length of end zones / total length of field

= (10+10)/(100+10+10)

=20/120

=1/6

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What’s the slope for RS

Annette [7]

Answer: 4/2

Step-by-step explanation: Rise over run. From point S to R it goes up 4 and over 2.

6 0

3 years ago

Indicate whether the function represents an exponential growth or decay.

svetoff [14.1K]

Answer:

1) decay

2) growth

3) growth

Step-by-step explanation:

A generic exponential function can be written as:

f(x) = A*(r)^x

Where:

A is the initial amount of something.

r is the rate of growth.

x is the variable, usually, represents time.

if r > 1, we have an exponential growth.

if r < 1, we have an exponential decay.

1) f(x) = (3/4)^x

in this case we have:

A = 1

r = (3/4) = 0.75

Clearly, r < 1.

Then this is an exponential decay.

2) f(x) = (1/6)*4^x

In this case we have:

A = (1/6)

r = 4

Here we have r > 1.

Then this is an exponential growth.

3) f(x) = (1/4)*(5/2)^x

in this case we have:

A = 1/4

r = 5/2 = 2.5

here we have r > 1, then this is an exponential growth.

8 0

3 years ago

Determine if the columns of the matrix form a linearly independent set. Justify your answer. [Start 3 By 4 Matrix 1st Row 1st Co

Volgvan

Answer:

Linearly Dependent for not all scalars are null.

Step-by-step explanation:

Hi there!

1)When we have vectors like $v_{1},v_{2},v_{3}, ...$ we call them linearly dependent if we have scalars $a_{1},a_{2},a_{3},...$ as scalar coefficients of those vectors, and not all are null and their sum is equal to zero.

$a_{1}\vec{v_{1}}+a_{2}\vec{v_{2}}+a_{3}\vec{v_{3}}+...a_{m}\vec{v_{m}}=0$

When all scalar coefficients are equal to zero, we can call them linearly independent

2) Now let's examine the Matrix given:

$\begin{bmatrix}1 &-2 &2 &3 \\ -2 & 4 & -4 &3 \\ 0&1 &-1 & 4\end{bmatrix}$

So each column of this Matrix is a vector. So we can write them as:

$\vec{v_{1}}=\left \langle 1,-2,1 \right \rangle,\vec{v_{2}}=\left \langle -2,4,-1 \right \rangle,\vec{v_{3}}=\left \langle 2,-4,4 \right \rangle\vec{v_{4}}=\left \langle 3,3,4 \right \rangle$ Or

Now let's rewrite it as a system of equations:

$a_{1}\begin{bmatrix}1\\ -2\\ 0\end{bmatrix}+a_{2}\begin{bmatrix}-2\\ 4\\ 1\end{bmatrix}+a_{3}\begin{bmatrix}2\\ -4\\ -1\end{bmatrix}+a_{4}\begin{bmatrix}3\\ 3\\ 4\end{bmatrix}=\begin{bmatrix}0\\ 0\\ 0\end{bmatrix}$

2.1) Since we want to try whether they are linearly independent, or dependent we'll rewrite as a Linear system so that we can find their scalar coefficients, whether all or not all are null.

Using the Gaussian Elimination Method, augmenting the matrix, then proceeding the calculations, we can see that not all scalars are equal to zero. Then it is Linearly Dependent.

$\left ( \left.\begin{matrix}1 &-2 &2 &3 \\ -2 &4 &-4 &3 \\ 0 & 1 &-1 &4 \\ \end{matrix}\right|\begin{matrix}0\\ 0\\ 0\end{matrix} \right )R_{1}\times2 +R_{2}\rightarrow R_{2}\left ( \left.\begin{matrix}1 &-2 &2 &3 \\ 0 &0 &9 &0\\ 0 & 1 &-1 &4 \\ \end{matrix}\right|\begin{matrix}0\\ 0\\ 0\end{matrix} \right )\ R_{2}\Leftrightarrow R_{3}\left ( \left.\begin{matrix}1 &-2 &2 &3 \\ 0 &1 &-1 &4 \\ 0 &0 &9 &0 \\ \end{matrix}\right|\begin{matrix}0\\ 0\\ 0\end{matrix} \right )$ $\left\{\begin{matrix}1a_{1} &-2a_{2} &+2a_{3} &+3a_{4} &=0 \\ &1a_{2} &-1a_{3} &+4a_{4} &=0 \\ & & &9a_{4} &=0 \end{matrix}\right.\Rightarrow a_{1}=0, a_{2}=a_{3},a_{4}=0$