Refer to Exercise 12.5. Consider two methods for selecting the dosages. Method 1 assigns three rats to the dosage x = 2 and three rats to x = 5. Method 2 equally spaces the dosages between x = 2 and x = 5 (x = 2, 2.6, 3.2, 3.8, 4.4, and 5.0). Suppose that σ is known and that the relationship between E(Y) and x is truly linear (see Chapter 11). If we use the data from both methods to construct confidence intervals for the slope β1, which method will yield the longer interval? How much longer is the longer interval? If we use method 2, approximately how many observations will be required to obtain an interval the same length as that obtained by the optimal assignment of method 1?
12.5 Suppose that we wish to study the effect of the stimulant digitalis on the blood pressure Y of rats over a dosage
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Mathematical Statistics with Applications
- The data given below indicate the existence of a linear relationship between the x and y variables. Suppose an analyst who prepared the solutions and carried out the RI measurements was not skilled and as a result of poor technique, allowed intermediate errors to appear. The results are the following:Concentration of solution in percent (x) 10 26 33 50 61Refractive indices (y) 1.497 1.493 1.485 1.478 1.477Step 1. Carefully plot the given x and y values (from the table) on a regular graphing paper. Label then connect the points to observe a zigzag plot due to the scattered points. Step 2: Copy and fill the table given below: x (x - x̄) (x - x̄) 2 y (y - ȳ) (y - ȳ) 2 (x - x̄) (y - ȳ) 10 1.497 26 1.49333 1.48550 1.47861 1.477∑ = ∑ = ∑ = ∑ = ∑ = ∑ = ∑ =x̄= ∑xi ÷ Nx̄= ȳ = ∑yi ÷ Nȳ = Step 3. After completing the table, present following computations and the interpretation.a. Calculate the correlation coefficient (r), using the working formula: r =Σ (x − x ) (y − ȳ)√(Σ(x − x )2)(Σ(y −…arrow_forwardGiven datasets X: x1 (1, 4), x2 (2, 3), x3 (3, 4), and x4 (5, -3), x5 (6, -1), x6 (7, -1) with label y = (- 1, -1, -1, 1, 1, 1) respectively, find analytically hard margin W and bias b so that you will be able to determine linear discriminant function f(X) = WT . X + b. You may need to draw the points and estimate the boundary decision function that may be used to help you to make a very first guess the parameter W and b. Once you found the correct discriminant function f(X) = WT . X + b, test your function to correctly classify x1 (1, 4) and x4 (5, -3). Please thoroughly describe.arrow_forwardThe table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. xx 11.8 8.6 7.1 3.9 2.5 2.6 2.4 0.4 yy 14.3 11.5 9.8 7.6 6.2 6.5 6.4 4.1 xx = thousands of automatic weaponsyy = murders per 100,000 residentsThis data can be modeled by the equation y=0.86x+4.07.y=0.86x+4.07. Use this equation to answer the following; Special Note: I suggest you verify this equation by performing linear regression on your calculator.A) How many murders per 100,000 residents can be expected in a state with 3 thousand automatic weapons?Answer = Round to 3 decimal places.B) How many murders per 100,000 residents can be expected in a state with 4.1 thousand automatic weapons?Answer = Round to 3 decimal places.arrow_forward
- ch 11. 4 Oxnard Petro, Ltd., has three interdisciplinary project development teams that function on an ongoing basis. Team members rotate from time to time. Every 4 months (three times a year) each department head rates the performance of each project team (using a 0 to 100 scale, where 100 is the best rating). Are the main effects significant? Is there an interaction?arrow_forward2- An expert estimates that the distribution parameter for durability times of parts produced with machine A in the factory is different from the distribution parameter for durability times of parts produced with machine B. Durability times of 4 parts produced from machine A and 4 parts produced from machine B are given below. Find the Mann-Whitney U value by using these data. a) 18 B) 6 NS) 16 D) 20 TO) 12arrow_forwardFor some genetic mutations, it is thought that the frequency of the mutant gene in men increases linearly with age. If m1 is the frequency at age t1, and m2 is the frequency at age t2, then the yearly rate of increase is estimated by r = (m2 − m1)/(t2 − t1). In a polymerase chain reaction assay, the frequency in 20-year-old men was estimated to be 17.7 ± 1.7 per μgDNA, and the frequency in 40-year-old men was estimated to be 35.9 ± 5.8 per μg DNA. Assume that age is measured with negligible uncertainty.a) Estimate the yearly rate of increase, and find the uncertainty in the estimate.b) Find the relative uncertainty in the estimated rate of increase.arrow_forward
- The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. xx 11.3 8.6 7.1 3.3 2.4 2.3 2.4 0.7 yy 13.7 11.1 10.4 6.9 6.4 6.2 6.1 4.9 xx = thousands of automatic weaponsyy = murders per 100,000 residentsThis data can be modeled by the equation y=0.83x+4.28.y=0.83x+4.28. Use this equation to answer the following;Special Note: I suggest you verify this equation by performing linear regression on your calculator.A) How many murders per 100,000 residents can be expected in a state with 10.7 thousand automatic weapons?Answer = Round to 3 decimal places.B) How many murders per 100,000 residents can be expected in a state with 1.6 thousand automatic weapons?Answer = Round to 3 decimal places.The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. xx 11.3 8.6 7.1 3.3 2.4 2.3 2.4 0.7 yy 13.7 11.1 10.4 6.9 6.4 6.2 6.1 4.9 xx = thousands of…arrow_forwardBased on the below table, compute the regression line that predicts Y from X. (relevant section) MX MY sX sY r 10 12 2.5 3.0 -0.6arrow_forwardRefer to Exercise 7. Assume that p = 4.3 ± 0.1 cm and q = 2.1 ± 0.2 cm. Estimate f, and find the relative uncertainty in the estimate.arrow_forward
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