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3 years ago

For a polynomial p(x), the value of p(3) is −2. Which of the following must be true about p(x)?

Mathematics

1 answer:

mr Goodwill [35]3 years ago

8 0

Answer:

Step-by-step explanation:

The factor theorem states if (x - h) is a factor of a polynomial p(x) then

p(h) = 0

However, p(h) ≠ 0 then the value obtained is the remainder.

Thus

p(3) = - 2

When p(x) is divided by (x - 3) then the remainder is - 2

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Solve the equation for all values of x in simplest form (x + 3)^2 = -16

Arlecino [84]

Answer:

x = -7 or x = 1

Step-by-step explanation:

Given expression:

(x + 3)² = -16

Problem;

Solve for x;

Solution:

To solve for x; we use the factorization method;

Take -16 to the left of the equation;

(x + 3)² = -16

(x + 3)² + 16 = 0

(x+ 3)² + 4² = 0

if x² + y² = (x + y)(x - y)

So;

(x + 3 + 4) (x + 3 - 4) = 0

(x + 7)(x - 1) = 0

x + 7 = 0 or x - 1 = 0

x = -7 or x = 1

6 0

3 years ago

The image shows a geometric representation of the function f(x)=x^2-2x-6 written in standard form. What is the function written

Degger [83]

Y=(x-1)^2-7 This is this function in vertex form

9 0

3 years ago

Read 2 more answers

#10 i The table shows the admission costs (in dollars) and the average number of daily visitors at an amusement park each the pa

lions [1.4K]

The line of best fit is a straight line that can be used to predict the

average daily attendance for a given admission cost.

Correct responses:

The equation of best fit is; $\underline{ \hat Y = 1,042 - 4.9 \cdot X_i}$

The correlation coefficient is; r ≈<u> -0.969</u>

<h3>Methods by which the line of best fit is found</h3>

The given data is presented in the following tabular format;

$\begin{tabular}{|c|c|c|c|c|c|c|c|c|}Cost, (dollars), x&20&21&22&24&25&27&28&30\\Daily attendance, y&940&935&940&925&920&905&910&890\end{array}\right]$

The equation of the line of best fit is given by the regression line

equation as follows;

$\hat Y = \mathbf{b_0 + b_1 \cdot X_i}$

Where;

$\hat Y$ = Predicted value of the<em> i</em>th observation

b₀ = Estimated regression equation intercept

b₁ = The estimate of the slope regression equation

$X_i$ = The <em>i</em>th observed value

$b_1 = \mathbf{\dfrac{\sum (X - \overline X) \cdot (Y - \overline Y) }{\sum \left(X - \overline X \right)^2}}$

$\overline X$ = 24.625

$\overline Y$ = 960.625

$\mathbf{\sum(X - \overline X) \cdot (Y - \overline Y)} = -433.125$

$\mathbf{\sum(X - \overline X)^2} = 87.875$

Therefore;

$b_1 = \mathbf{\dfrac{-433.125}{87.875}} \approx -4.9289$

Therefore;

The slope given to the nearest tenth is b₁ ≈ -4.9

$b_0 = \mathbf{\dfrac{\left(\sum Y \right) \cdot \left(\sum X^2 \right) - \left(\sum X \right) \cdot \left(\sum X \cdot Y\right)} {n \cdot \left(\sum X^2\right) - \left(\sum X \right)^2}}$

By using MS Excel, we have;

n = 8

∑X = 197

∑Y = 7365

∑X² = 4939

∑Y² = 6782675

∑X·Y = 180930

(∑X)² = 38809

Therefore;

$b_0 = \dfrac{7365 \times 4939-197 \times 180930}{8 \times 4939 - 38809} \approx \mathbf{1041.9986}$

The y-intercept given to the nearest tenth is b₀ ≈ 1,042

The equation of the line of best fit is therefore;

$\underline{\hat Y = 1042 - 4.9 \cdot X_i}$

The correlation coefficient is given by the formula;

$\displaystyle r = \mathbf{\dfrac{\sum \left(X_i - \overline X) \cdot \left(Y - \overline Y \right)}{ \sqrt{\sum \left(X_i - \overline X \right)^2 \cdot \sum \left(Y_i - \overline Y \right)^2} }}$