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2 years ago

Is 5.243 greater, equal to ,or less than 5.4?

Mathematics

2 answers:

FinnZ [79.3K]2 years ago

8 0

5.243 is less than 5.4

larisa [96]2 years ago

7 0

Answer:

5.243 is less than 5.4....

You might be interested in

Stacey and Jeremy sent out 380 invitations They have received 127 responses. What does q represent in the equation 380- q = 127

Maslowich

Q represents how many they did NOT recieve

380-127= 253

Now let's check

380-253= 127

CHECK

So q represents 253(the number of invitations they did NOT recieve)

Hope this helps!

7 0

2 years ago

Simplify by factoring. What are the excluded values? Choose all that apply.

makvit [3.9K]

Answer:

x = -2

x = 8

Step-by-step explanation:

Excluded values are the ones which make the denominator zero

3x² + x - 10

3x² + 6x - 5x - 10

3x(x + 2) - 5(x + 2)

(x + 2)(3x - 5)

x² - 6x - 16

x² - 8x + 2x - 16

x(x - 8) + 2(x - 8)

(x - 8)(x + 2)

[(x + 2)(3x - 5)] ÷ [(x - 8)(x + 2)]

(3x - 5)/(x - 8)

So excluded values are 8, -2

6 0

3 years ago

Two cars traveling toward each other are 250 miles apart. Car a is traveling 15 miles per hour faster than car

Anon25 [30]

Let car b be travelling at x mph. as they are travelling towards each other their speed of approach is (x + x + 15 ) mph. So we have the equation

speed = distance / time

2x + 15 = 250 / 2

2x = 125 - 15 = 110

x = 55 mph

Car b travels at 55 mph and car a travels at 70 mph Answer

3 0

2 years ago

All vectors are in Rn. Check the true statements below:

Oduvanchick [21]

Answer:

A), B) and D) are true

Step-by-step explanation:

A) We can prove it as follows:

$Proy_{cv}y=\frac{(y\cdot cv)}{||cv||^2}cv=\frac{c(y\cdot v)}{c^2||v||^2}cv=\frac{(y\cdot v)}{||v||^2}v=Proy_{v}y$

B) When you compute the product Ax, the i-th component is the matrix of the i-th column of A with x, denote this by Ai x. Then, we have that $||Ax||=\sqrt{(A_1 x)^2+\cdots (A_n x)^2}$ . Now, the colums of A are orthonormal so we have that (Ai x)^2=x_i^2. Then $||Ax||=\sqrt{(x_1)^2+\cdots (x_n)^2}=||x||$ .

C) Consider $S=\{(0,2),(2,0)\}\subseteq \mathbb{R}^2$ . This set is orthogonal because $(0,2)\cdot(2,0)=0(2)+2(0)=0$ , but S is not orthonormal because the norm of (0,2) is 2≠1.

D) Let A be an orthogonal matrix in $\mathbb{R}^n$ . Then the columns of A form an orthonormal set. We have that $A^{-1}=A^t$ . To see this, note than the component $b_{ij}$ of the product $A^t A$ is the dot product of the i-th row of $A^t$ and the jth row of $A$ . But the i-th row of $A^t$ is equal to the i-th column of $A$ . If i≠j, this product is equal to 0 (orthogonality) and if i=j this product is equal to 1 (the columns are unit vectors), then $A^t A=I$

E) Consider S={e_1,0}. S is orthogonal but is not linearly independent, because 0∈S.

In fact, every orthogonal set in R^n without zero vectors is linearly independent. Take a orthogonal set $\{u_1,u_2\cdots u_p\}$ and suppose that there are coefficients a_i such that $a_1u_1+a_2u_2\cdots a_nu_n=0$ . For any i, take the dot product with u_i in both sides of the equation. All product are zero except u_i·u_i=||u_i||. Then $a_i||u_i||=0$ then $a_i=0$ .

5 0

3 years ago

You pay for a $500 purchase using a credit card. The credit card company charges a 24% interest rate, compounded monthly ,on the

mezya [45]

Answer:

530.60 for interest on 3 months you don't make any payments

3 0

2 years ago