Ask question

Ask question

All categories

2 years ago

13

The domain of the function is the set of all real numbers, and the range of the function is the set of all real numbers greater

than or equal to

1 answer:

aleksklad [387]2 years ago

8 0

Hnuxndmkatsbdjduhsnz
If

You might be interested in

Solve x^2 +3x=0 by factoring

ivolga24 [154]

Answer:

x=0,-3 hope this helps

https://www.symbolab.com/solver/step-by-step/x%5E%7B2%7D%20%2B3x%3D0%20 here this website to show your work hope this helps

3 0

3 years ago

Write a linear inequality in two variables that has (-1, 3) as a solution but does not have (4,0) as a solution.

Stels [109]

Answer: y ≤ -x + 2

<u>Step-by-step explanation:</u>

There are an infinite number of possible solutions.

Plot the two points, draw any line between them such that the two points are NOT connected, then choose the inequality symbol that shades (-1, 3).

Here is one solution that satisfies the requirements. y ≤ -x + 2

Here is another: y < -x + 3

And another: y > x + 3

And one more: y ≥ x + 4

3 0

3 years ago

#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;

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

Where;

$\sqrt{\sum \left(X - \overline X \right)^2 \times \sum \left(Y - \overline Y \right)^2} = \mathbf{446.8121}$

$\sum \left(X_i - \overline X \right) \times \left(Y - \overline Y\right) = \mathbf{-433.125}$

Which gives;

$r = \dfrac{-433.125}{446.8121} \approx \mathbf{-0.969367213}$

The correlation coefficient given to the nearest thousandth is therefore;

<u>Correlation coefficient, r ≈ -0.969</u>

Learn more about regression analysis here:

brainly.com/question/14279500

7 0

2 years ago

Sold 685 boxes of cookies about how many boxes are they sold rounded to the nearest ten

MissTica

Answer:

690

Step-by-step explanation:

Round from the tens place.

8 0

3 years ago

What is the slope of (4,1) and (6,-1)

schepotkina [342]

Answer:

slope = -1

Step-by-step explanation:

you <u>subtract the y-values</u> (-1-1=-2) then <u>subtract the x-values</u> (6-4=2) then divide the sum of the y-values by the sum of the x-values

$\frac{-2}{2}$ which simplifies to a slope of -1

6 0

2 years ago