Welcome to Westonci.ca, your one-stop destination for finding answers to all your questions. Join our expert community now! Explore comprehensive solutions to your questions from knowledgeable professionals across various fields on our platform. Get quick and reliable solutions to your questions from a community of experienced experts on our platform.

Assume you have noted the following prices for books and the number of pages that each book contains.Book Pages (x) Price (y)A 500 $7.00B 700 7.50C 750 9.00D 590 6.50E 540 7.50F 650 7.00G 480 4.50a. Develop a least-squares estimated regression line.b. Compute the coefficient of determination and explain its meaning.c. Compute the correlation coefficient between the price and the number of pages. Test to see if x and y are related. Use ? = 0.10.

Sagot :

[tex]a) $y=0.00991 x+1.042$b) $r^2=0.7503^2=0.563$\\C) $r=\frac{7(30095)-(4210)(49)}{\sqrt{\left[7(2595100)-(4210)^2\right]\left[7(354)-(49)^2\right]}}=0.7503$[/tex]

x: 500, 700, 750, 590 , 540, 650, 480

y: 7.00, 7.50 , 9.00, 6.5, 7.50 , 7.0, 4.50

We want to create a linear model like this :

[tex]$y=m x+b$[/tex]

Where

[tex]$m=\frac{S_{x y}}{S_{x x}}$[/tex]

And:  

[tex]$\begin{aligned}& S_{x y}=\sum_{i=1}^n x_i y_i-\frac{\left(\sum_{i=1}^n x_i\right)\left(\sum_{i=1}^n y_i\right)}{n} \\& S_{x x}=\sum_{i=1}^n x_i^2-\frac{\left(\sum_{i=1}^n x_i\right)^2}{n}\end{aligned}$[/tex]

With these we can find the sums:  

[tex]$\begin{aligned}& S_{x x}=\sum_{i=1}^n x_i^2-\frac{\left(\sum_{i=1}^n x_i\right)^2}{n}=2595100-\frac{4210^2}{7}=63085.714 \\& S_{x y}=\sum_{i=1}^n x_i y_i-\frac{\left(\sum_{i=1}^n x_i\right)\left(\sum_{i=1}^n y_i\right) n}{=} 30095-\frac{4210 * 49}{7}=625\end{aligned}$[/tex]

And the slope would be:  

[tex]m=\frac{625}{63085.714}=0.00991[/tex]

Now we can find the means for x and y like this:

[tex]$\begin{aligned}& \bar{x}=\frac{\sum x_i}{n}=\frac{4210}{7}=601.429 \\& \bar{y}=\frac{\sum y_i}{n}=\frac{49}{7}=7\end{aligned}$[/tex]

And we can find the intercept using this:

[tex]$b=\bar{y}-m \bar{x}=7-(0.00991 * 601.429)=1.042$[/tex]

And the line would be:

[tex]$y=0.00991 x+1.042$[/tex]

Part b

The correlation coefficient is given by:

[tex]r=\frac{n\left(\sum x y\right)-\left(\sum x\right)\left(\sum y\right)}{\sqrt{\left[n \sum x^2-\left(\sum x\right)^2\right]\left[n \sum y^2-\left(\sum y\right)^2\right]}}[/tex]

For our case we have this:

[tex]$\begin{aligned}& \mathrm{n}=7 \sum x=4210, \sum y=49, \sum x y=30095, \sum x^2=2595100, \sum y^2=354 \\& r=\frac{7(30095)-(4210)(49)}{\sqrt{\left[7(2595100)-(4210)^2\right]\left[7(354)-(49)^2\right]}}=0.7503\end{aligned}$[/tex]

The determination coefficient is given by:

[tex]$r^2=0.7503^2=0.563$[/tex]

Part c

[tex]r=\frac{7(30095)-(4210)(49)}{\sqrt{\left[7(2595100)-(4210)^2\right]\left[7(354)-(49)^2\right]}}=0.7503[/tex]

Learn more about regression line to visit this link

https://brainly.com/question/7656407

#SPJ4

Thank you for your visit. We're committed to providing you with the best information available. Return anytime for more. Thanks for using our service. We're always here to provide accurate and up-to-date answers to all your queries. Westonci.ca is your go-to source for reliable answers. Return soon for more expert insights.