Question #271645

An experiment was conducted to study the effect of pesticides on plant species that are exposed to them. Different dosages of pesticides were administered to 4 groups of 4 mice. The 16 mice were females of similar age and condition. One group received no pesticides. The response Y was measure of brain activity. It was postulated that brain activity (Y in moles/liters per minute) would decrease with an increase in dosage (X in mg/kg body weight)


Dose (X)

0.0, 0.0, 0.0, 0.0, 2.5, 2.5, 2.5, 2.5


Activity (Y)

10.6, 10.4, 10.8, 11.0, 11.0, 11.3, 10.3, 9.9


Dose (X)

5.0, 5.0, 5.0, 5.0, 7.5, 7.5, 7.5, 7.5


Activity (Y)

9.5, 9.2, 9.7, 8.6, 8.2, 8.0, 8.4, 7.8




a) test if there is a significant linear relationship between the dose and the brain activity by constructing an analysis of variance table for the above data.




b) compute r and interpret the result.



1
Expert's answer
2021-12-29T17:38:12-0500

a)

Regression ANOVA:

H0:Y=b0H_0:Y=b_0 , there is no a significant linear relationship between the dose and the brain activity 

Ha:Y=b0+b1XH_a:Y=b_0+b_1X , there is a significant linear relationship between the dose and the brain activity


Regression line equation:

Y^=b0+b1XŶ = b_0 +b_1X

b1=Σ(xixˉ)(yiyˉ)Σ(xixˉ)2=0.367b_1 = \frac{ Σ(x_i-x̄)(y_i-ȳ)}{ Σ(x_i-x̄)^2}=-0.367

b00=yˉb1xˉ=11.045b_00 = ȳ - b_1x̄=11.045

Y^=11.0450.367XŶ = 11.045 - 0.367X


for Regression:

df = p(number of variables) - number of independent variables = 1

Sum of Square:

SSregression=(y~iy)2=16.8361SS_{regression}=\sum (\tilde{y}_i-\overline{y})^2=16.8361

where y~i\tilde{y}_i are predicted values

Mean Square:

MSregression=SSregression/(p1)=16.8361MS_{regression}=SS_{regression}/(p-1)=16.8361


for Residual:

df=n11=14df=n-1-1=14

n is total number of observations

Sum of Square:

SSresidual=(yiy~i)2=3.9382SS_{residual}=\sum (y_i-\tilde{y}_i)^2=3.9382

Mean Square:

MSresidual=SSresidual/(n11)=0.2813MS_{residual}=SS_{residual}/(n-1-1)=0.2813


F Statistic:

F=MSregression/MSresidual=59.85F=MS_{regression}/MS_{residual}=59.85


critical value for α=0.05\alpha=0.05 :

F(1,14)=4.6001F_{(1,14)}=4.6001


Since F>F(1,14)F>F_{(1,14)} we reject null hypothesis. There is a significant linear relationship between the dose and the brain activity.


b.

correlation coefficient:


r=Σ(xixˉ)(yiyˉ)(Σ(xixˉ)2Σ(yiyˉ)2)=0.9002r=\frac{Σ(x_i - x̄)(y_i - ȳ)}{ \sqrt{(Σ(x_i - x̄)^2Σ(y_i - ȳ)^2 )}} =-0.9002


there is a very strong inverse relationship between the dose and the brain activity


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