Rob found that the coefficient of determination between the length of essays submitted to a teacher x and the score the teacher
1 answer:
Answer:
The coefficient of determination is used to measure how well a model fits the real data, or how well it can replicate them. The closer to 1 the value of R ^ 2 the more accurate the model is.
In this case, that R ^ 2 = 0.661 means that the model fits moderately to the variable to be studied.
For a linear regression model, the coefficient of determination is the square of the correlation coefficient r of Pearson. So:
r = 0.813
This value of r close to 1 means that the length of the essays sent to a teacher (x) and the score that the teacher gave to the essay (and) are highly related.
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The second matrix represents the triangle dilated by a scale factor of 3.
Step-by-step explanation:
Step 1:
To calculate the scale factor for any dilation, we divide the coordinates after dilation by the same coordinated before dilation.
The coordinates of a vertice are represented in the column of the matrix. Since there are three vertices, there are 2 rows with 3 columns. The order of the matrices is 2 × 3.
Step 2:
If we form a matrix with the vertices (-2,0), (1,5), and (4,-8), we get
The scale factor is 3, so if we multiply the above matrix with 3 throughout, we will get the matrix that represents the vertices of the triangle after dilation.
Step 3:
The matrix that represents the triangle after dilation is given by
This is the second option.