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You are given the accompanying response data on concentration of a chemical as a function of time. The six sets of observations Y1 to Y6represent different environmental conditions.
Time (h) Y1 Y2 Y3 Y4 Y5 Y66 .38 .20 .34 .43 .10 .2612 .74 .34 .69 .82 .16 .4824 .84 .51 .74 .87 .18 .5148 .70 .41 .62 .69 .19 .4472 .43 .29 .43 .60 .15 .33
(a) Use cubic polynomial models to relate Y = concentration to X = time, where each environment is allowed to have its own intercept and response curve. Is the cubic term significant for any of the environments? [For the purposes of testing homogeneity in Part (c), retain the minimum-degree polynomial model that describes all responses.]
(b) Your knowledge of the process tells you that Y must be zero when X = 0. Test the composite null hypothesis that the six intercepts are zero using the model in Part (a) as the full model.
What model do you adopt based on this test?
(c) Use the model determined from the test in Part (b) and test the homogeneity of the six response curves. State the conclusion of the test and give the model you have adopted at this stage.
Find out the probability
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Graph the p.d.f and show that the probability of the part failing in the first 200 weeks is 1/8
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The owner of a local night club has recently surveyed a random sample of n=250 customers of the club. She would now like to determine whether or not the mean age of her customers is over 30.
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Can you cite published examples for one or more countries or regions? Can you think of other cases where the expected probabilities do not quite agree with the empirical values based on relative frequency?
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