.   y=____+______x (Round to two decimal places as​ needed.)​   2. Identify a characteristic of the data that is ignored by the regression line.   A.There is no trend in the data.   B.The data has a pattern that is not a straight line.   C.There is an influential point that strongly affects the graph of the regression line.   D.There is no characteristic of the data that is ignored by the regression line.

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Chapter1: Starting With Matlab
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​1.   y=____+______x (Round to two decimal places as​ needed.)​
 
2. Identify a characteristic of the data that is ignored by the regression line.
 
A.There is no trend in the data.
 
B.The data has a pattern that is not a straight line.
 
C.There is an influential point that strongly affects the graph of the regression line.
 
D.There is no characteristic of the data that is ignored by the regression line.
Use the given data to find the equation of the regression line. Examine the scatterplot and identify a characteristic of
the data that is ignored by the regression line.
7
13
12
11
3
5
10
4
8
У 8.05
8.31
9.25
8.96
9.34
2.31
7.04
5.74
9.44
4.16
8.80
%3D
+ x (Round to two decimal places as needed.)
Transcribed Image Text:Use the given data to find the equation of the regression line. Examine the scatterplot and identify a characteristic of the data that is ignored by the regression line. 7 13 12 11 3 5 10 4 8 У 8.05 8.31 9.25 8.96 9.34 2.31 7.04 5.74 9.44 4.16 8.80 %3D + x (Round to two decimal places as needed.)
Expert Solution
Answer

We have used the excel data analysis tool to run the regression analysis.

x y (x-xbar) (x-xbar)^2 (y-ybar) (y-ybar)^2 (x-xbar)*(y-ybar)
7 8.05 -1 1 0.65 0.4225 -0.65
13 8.31 5 25 0.91 0.8281 4.55
9 9.25 1 1 1.85 3.4225 1.85
12 8.96 4 16 1.56 2.4336 6.24
11 9.34 3 9 1.94 3.7636 5.82
3 2.31 -5 25 -5.09 25.9081 25.45
6 7.04 -2 4 -0.36 0.1296 0.72
5 5.74 -3 9 -1.66 2.7556 4.98
10 9.44 2 4 2.04 4.1616 4.08
4 4.16 -4 16 -3.24 10.4976 12.96
8 8.8 0 0 1.4 1.96 0

 

The slope is given by

\beta_{1}= \frac{\sum (x - \overline{x})(y - \overline{y})}{\sum (x - \overline{x})^2}

\beta_{1}=\frac{66}{110} =0.6

 

The intercept is given by

\beta_{0} = \overline{y} -\beta_{1}\overline{x}

\beta_{0} = 7.4-8\times 0.6= 2.6​​​​​​​

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