Answer: He will have 8 1/3 nuts
Step-by-step explanation:
Amount of peanuts=4 2/3 cups
Amount of cashews=3 2/3 cups
Combing the nuts will give Total amount of nuts ( peanuts and cashews)
=4 2/3 +3 2/3
=7 4/3
7 + 1 1/3
8 1/3 nuts
Y=3/5x+5
hope this helps!!
Going across like a horizon
Answer:
You did not provide the tables to choose from, but the relationship between number of books and total price is that each book is 14.25. Hope that helps at least.
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;
![\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]](https://tex.z-dn.net/?f=%5Cbegin%7Btabular%7D%7B%7Cc%7Cc%7Cc%7Cc%7Cc%7Cc%7Cc%7Cc%7Cc%7C%7DCost%2C%20%28dollars%29%2C%20x%2620%2621%2622%2624%2625%2627%2628%2630%5C%5CDaily%20attendance%2C%20y%26940%26935%26940%26925%26920%26905%26910%26890%5Cend%7Barray%7D%5Cright%5D)
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