Do the linest fit, and match each statistical quantity with its value Question 1 options: 1.997 7 8.81 0.16 3.86 0.86 1. The slope (gradient) of the line 2. The y-intercept which is the value of y when x=0 3. The standard error value for the slope value 4. The standard error value for the y-intercept 5. The number of degrees of freedom 6. The residual sum of squares Question 2 (1 point)

Step-by-step explanation:

Hello!

Full text in attachment.

Given the data of the dependent variable Y and the independent variable X,

you have to estimate the linear regression: ^Y= a + bX

Where "a" is the estimate of the intercept and "b" is the estimate of the slope.

n= 9

∑X= 42.70; ∑X²= 250.45; ∑Y= 120.05; ∑Y²= 1801.03; ∑XY= 665.16

Y[bar]= 13.34; X[bar]= 4.74

Using the software I've calculated the asked values:

The slope of the line is

The value of the Y-intercept is a= Y[bar] -bX[bar]= 13.34-1.997*4.74= 3.86

The standard error of the slope is Sb= 0.16

The standard error of the Y-intercept is Sa= 0.86

The degrees of freedom for the hypothesis test for the slope (t-test) are n-2= 9-2= 7

The SSresidues= 8.81

I hope this helps!

b

12.4, 12.387, 12.26, 12.252, 6.241, 6.2, 6.015, 6.009, 1.411, 1.2, 1.056, 1.007, 0.31,   0.13, 0.5, 0.04

step-by-step explanation:

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