30 POINTS

use Taylor's Theorem with integral remainder and the mean-value theorem for integrals to deduce Taylor's Theorem with lagrange r

Vadim26 [7]

Answer:

As consequence of the Taylor theorem with integral remainder we have that

$f(x) = f(a) + f'(a)(x-a) + \frac{f''(a)}{2!}(x-a)^2 + \cdots + \frac{f^{(n)}(a)}{n!}(x-a)^n + \int^a_x f^{(n+1)}(t)\frac{(x-t)^n}{n!}dt$

If we ask that $f$ has continuous $(n+1)$ th derivative we can apply the mean value theorem for integrals. Then, there exists $c$ between $a$ and $x$ such that

$\int^a_x f^{(n+1)}(t)\frac{(x-t)^k}{n!}dt = \frac{f^{(n+1)}(c)}{n!} \int^a_x (x-t)^n d t = \frac{f^{(n+1)}(c)}{n!} \frac{(x-t)^{n+1}}{n+1}\Big|_a^x$

Hence,

$\int^a_x f^{(n+1)}(t)\frac{(x-t)^k}{n!}d t = \frac{f^{(n+1)}(c)}{n!} \frac{(x-t)^{(n+1)}}{n+1} = \frac{f^{(n+1)}(c)}{(n+1)!}(x-a)^{n+1} .$

Thus,

$\int^a_x f^{(n+1)}(t)\frac{(x-t)^k}{n!}d t = \frac{f^{(n+1)}(c)}{(n+1)!}(x-a)^{n+1}$

and the Taylor theorem with Lagrange remainder is

$f(x) = f(a) + f'(a)(x-a) + \frac{f''(a)}{2!}(x-a)^2 + \cdots + \frac{f^{(n)}(a)}{n!}(x-a)^n + \frac{f^{(n+1)}(c)}{(n+1)!}(x-a)^{n+1}$ .

Step-by-step explanation:

5 0

3 years ago

Using the remainder theorem which quotient has a remainder of 20?

stealth61 [152]

Answer:

D

Step-by-step explanation:

When a polynomial f(x) is divided by (x - a) then remainder is f(a)

A

divided by (x + 4 ), then a = - 4

$(-4)^{4}$ - 8(- 4)² + 16 = 256 - 128 + 16 = 144 ≠ 20

B

divided by (x - 2), then a = 2

3(2)³ + 7(2)² + 5(2) + 2

= 3(8) + 7(4) + 10 + 2

= 24 + 28 + 12 = = 64 ≠ 20

C

divided by (x + 5) , then a = - 5

(- 5)³ + 5(- 5)² - 4(- 5) + 6

= - 125 + 125 + 20 + 6 = 26 ≠ 20

D

divided by (x - 2), then a = 2

3 $(2)^{4}$ - 5(2)³ + 5(2) + 2

= 3(16) - 5(8) + 10 + 2

= 48 - 40 + 12 = 20 ← Remainder of 20

3 0

2 years ago

In a survey of 300 college graduates, 53% reported that they entered a profession closely related to their college major. If 9 o

ExtremeBDS [4]

Answer:

0.1348 = 13.48% probability that 3 of them entered a profession closely related to their college major.

Step-by-step explanation:

For each graduate, there are only two possible outcomes. Either they entered a profession closely related to their college major, or they did not. The probability of a graduate entering a profession closely related to their college major is independent of other graduates. This, coupled with the fact that they are chosen with replacement, means that we use the binomial probability distribution to solve this question.

Binomial probability distribution

The binomial probability is the probability of exactly x successes on n repeated trials, and X can only have two outcomes.

$P(X = x) = C_{n,x}.p^{x}.(1-p)^{n-x}$