Computer output for fitting a simple linear model is given below. state the value of the sample slope for the given model. in testing if the slope in the population is different from zero, identify the p-value and use it (and a 5% significance level) to make a clear conclusion about the effectiveness of the model. the regression equation is : y= 93.9 - 6.86xpredictor coef se coef t pconstant 93.874 4.763 19.71 0.000x -6.8565 0.8001 -8.57 0.000sample slope: value: the model effective: yes or no

Sample Slope:_-6.8565_-P Value:__0.000___-Is the model effective: yes

Step-by-step explanation:

Hello!

The estimated regression equation is : Y= 93.9 - 6.86X

Where Y is the dependent variable and X is the independent variable.

                 PredictorCoef    SECoef        T          P

Constant   93.874                4.763      19.71      0.000

X                -6.8565             0.8001     -8.57      0.000

Looking at the data that corresponds to the estimation of the regression:

The row of "Constant " corresponds to the estimation regarding α (y-intercept of the line)

a= 93.874 (Point estimation of α)

Sa= 4.763 (Standard deviation of a)

T= 19.71 (Is the value of the corresponding statistic for the hypothesis H₀: α = 0 vs H₁: α ≠ 0)

And P= 0.000 is the P-value for the test mentioned above.

The row called "X" has all the information regarding the estimation of the slope.

b= -6.8565 (Point estimation of β)

Sb= 0.8001 (Standard deviation of b)

T= -8.57 (Is the value of the corresponding statistic for the hypothesis H₀: β = 0 vs H₁: β ≠ 0)

And P= 0.000 is the P-value for the test mentioned above.

With the given data, at a significance level of 5% the decision is to reject the null hypothesis (H₀: β = 0) which means that there is a modification of the population mean of the dependent variable when the independent variable varies in one unit. At the same level, you could say that the model is effective.

I hope it helps!

the answers c