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;
- 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;
The equation of the line of best fit is given by the regression line
equation as follows;
Where;
= Predicted value of the<em> i</em>th observation
b₀ = Estimated regression equation intercept
b₁ = The estimate of the slope regression equation
= The <em>i</em>th observed value
= 24.625
= 960.625
Therefore;
Therefore;
- The slope given to the nearest tenth is b₁ ≈ -4.9
By using MS Excel, we have;
n = 8
∑X = 197
∑Y = 7365
∑X² = 4939
∑Y² = 6782675
∑X·Y = 180930
(∑X)² = 38809
Therefore;
- The y-intercept given to the nearest tenth is b₀ ≈ 1,042
The equation of the line of best fit is therefore;
The correlation coefficient is given by the formula;
Where;
Which gives;
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
Answer:
The problem is 5 × 2/3 so
Billy paycheck every week was 2/3 a dollar which is approximately 66 cents but one day he did fantastic and got a raise and the raise was 5 times his last paycheck how much money is Billy new paycheck? So we do 5 × 2/3 and that equals 10/3, or 3 1/3, or 3 dollars and 30 cents.
Step-by-step explanation:
just copy and paste it.
Answer:
8/5
Step-by-step explanation:
First find h(-3)
h(-3)= 4-(-3) = 4+3 = 7
Then take this result and find g(h(-3)) = g(7)
g(7) = (7+1)/( 7-2) = 8/5
Answer: B
You can find slope by using the slope formula. Because we are already given two coordinate points, we can use that to find our slope. The slope formula is . This also refers to or 10/-4 or -5/2. Any coordinate with the x-value as 0 means that that coordinate is the y-intercept. Because (0,5) has 0 as its x-value, the y-intercept is 5.