Question

In: Statistics and Probability

(a) Write down the overall model form if one wishes to build a second order model...

(a) Write down the overall model form if one wishes to build a second order model for each value of the qualitative variable [5 points]

(c) Build a regression model showing the 90% confidence ranges of the regression parameters. Write down the mean estimates of the regression parameters for the model in (a)

(d) Write down the 90% bounds of the estimate of the y-intercept (constant term) [2 points]

(e) Compute the model prediction for a bulb with a dirty surface and with 1500 operation hours. [5 points]

(f) Perform one-way hypothesis testing for the existence of ?2 term, where ?2 is the qualitative input. Use ? = 0.05 [3 points]

Drop in light output percent (Output) Bulb surface (Qualitative input) Length of operation hours (Quantitative input)
0 Clean 0
16 Clean 400
22 Clean 800
27 Clean 1200
32 Clean 1600
36 Clean 2000
38 Clean 2400
0 Dirty 0
4 Dirty 400
6 Dirty 800
8 Dirty 1200
9 Dirty 1600
11 Dirty 2000
12 Dirty 2400

Solutions

Expert Solution

(a) y=b0+b1x+b2x2

y=Drop in light output percent (Output) and x=Length of operation hours (Quantitative input)

(c)y=1.2738+0.0183*x-3.6E-06*x2

(d)

Lower 90% Upper 90
-10.8200 13.3677

(e) for x=1500, y=1.2738+0.0183*1500-3.6E-06*1500*1500=20.6238

(f) here we use t-test and t=coefficient/SE(coefficient)=-3.6E-06/5.26E-06=-0.6859

the one-tailed critical t(0.05,11)=1.7959 is greater than absolute value of calculated t=0.6859, so x2 term is not significant and it may be removed from the model ( i.e. no existence)

following regression analysis information has been generated using ms-excel

SUMMARY OUTPUT
Regression Statistics
Multiple R 0.637572
R Square 0.406499
Adjusted R Square 0.298589
Standard Error 10.9107
Observations 14
ANOVA
df SS MS F Significance F
Regression 2 896.881 448.4405 3.767037 0.056730925
Residual 11 1309.476 119.0433
Total 13 2206.357
Coefficients Standard Error t Stat P-value Lower 90% Upper 90%
Intercept 1.27381 6.734228 0.189155 0.853417 -10.82008801 13.36770706
X 0.018348 0.013142 1.396123 0.190214 -0.005253775 0.041950204
X2 -3.6E-06 5.26E-06 -0.68591 0.506971 -1.3057E-05 5.83973E-06

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