In: Statistics and Probability
Here is data with y as the response variable.
| x | y | 
|---|---|
| 43.2 | 52.4 | 
| 52.8 | 58.7 | 
| 52.5 | 48.6 | 
| 189.8 | 112.4 | 
| 64.6 | 49.8 | 
| 47.6 | 57.2 | 
| 31.4 | 36.4 | 
| 66.6 | 60.1 | 
Make a scatter plot of this data. Which point is an
outlier?
Enter as an ordered pair. For example (a,b) - with
parenthesis.
Find the regression equation for the data set
without the outlier.
Enter as an equation of the form y=a+bxy=a+bx. Rounded to three
decimal places. For this WAMAP question, do not include the hat in
y-hat.
Find the regression equation for the data set with
the outlier.
Enter as an equation of the form y=a+bxy=a+bx. Rounded to three
decimal places. For this WAMAP question, do not include the hat in
y-hat.
Is this outlier an influential point? An influential point, when
removed from the data, will change the regression equation
drastically.

....................
(43.2, 52.4)
(52.8 , 58.7)
(52.5 , 48.6)
(189.8 ,112.4
(64.6 , 49.8)
(47.6 , 57.2)
(31.4 , 36.4)
(66.6 , 60.1)
)
| ΣX | ΣY | Σ(x-x̅)² | Σ(y-ȳ)² | Σ(x-x̅)(y-ȳ) | |
| total sum | 358.7 | 363.2 | 889.9571429 | 397.4 | 388.55 | 
| mean | 51.24 | 51.89 | SSxx | SSyy | SSxy | 
sample size ,   n =   7  
       
here, x̅ = Σx / n=   51.24   ,
    ȳ = Σy/n =   51.89  
          
       
SSxx =    Σ(x-x̅)² =    889.9571  
       
SSxy=   Σ(x-x̅)(y-ȳ) =   388.6  
       
          
       
estimated slope , ß1 = SSxy/SSxx =   388.6  
/   889.957   =   0.4366
          
       
intercept,   ß0 = y̅-ß1* x̄ =  
29.5131          
          
       
so, regression line is   Ŷ =  
29.513   +   0.437  
*x
.............
| ΣX | ΣY | Σ(x-x̅)² | Σ(y-ȳ)² | Σ(x-x̅)(y-ȳ) | |
| total sum | 548.2 | 475.6 | 17615.615 | 3601.6 | 7709.27 | 
| mean | 68.53 | 59.45 | SSxx | SSyy | SSxy | 
sample size ,   n =   8  
       
here, x̅ = Σx / n=   68.53   ,
    ȳ = Σy/n =   59.45  
          
       
SSxx =    Σ(x-x̅)² =    17615.6150  
       
SSxy=   Σ(x-x̅)(y-ȳ) =   7709.3  
       
          
       
estimated slope , ß1 = SSxy/SSxx =   7709.3  
/   17615.615   =   0.4376
          
       
intercept,   ß0 = y̅-ß1* x̄ =  
29.4608          
          
       
so, regression line is   Y =  
29.461   +   0.438   *x
...............
          
       
...................
THANKS
revert back for doubt
please upvote