Question:

People gain weight when they take in more energy from food than they expend. Some researchers wanted to investigate the link between obesity and energy spent on daily activity. Choose 20 healthy volunteers who don't exercise. Deliberately choose 10 who are lean and 10 who are mildly obese but still healthy. Attach sensors that monitor the subjects' every move for 10 days. The table below presents data on the time (in minutes per day) that the subjects spent standing or walking, sitting, and lying down. It can be concluded that mildly obese people spend less time standing and walking (on the average) than lean people. Is there a significant difference between the mean times the two groups spend lying down? Use the four-step process to answer this question from the data. (Let ?1 be the mean time spent lying down by the lean group, and ?2 be the mean time for the obese group.)?

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Time (minutes per day) spent in three different postures by lean?

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and obese subjectsGroupSubjectStand/WalkSitLieLean1 514.100365.300553.500Lean2 610.925372.512445.650Lean3 318.212586.138542.362Lean4 588.644356.144494.269Lean5 579.869344.994511.081Lean6 544.388381.312511.500Lean7 676.188271.188471.700Lean8 552.656325.219569.006Lean9 376.831539.031528.431Lean10 508.700526.838398.962Obese11 261.244641.281521.044Obese12 468.756456.644516.931Obese13 364.138577.662568.300Obese14 418.667573.662533.208Obese15 342.375583.662500.931Obese16 414.531567.556453.856Obese17 362.650619.262459.550Obese18 266.344650.181511.981Obese19 406.631571.769446.706Obese20 423.356591.369417.919?

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Find the size, mean and standard deviation n x s Lean Obese ?

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Calculate the test statistic. (Round your answer to three decimal places.)?

3.3 Given two independent Gaussian random variables U ~ N(-1, 1) and V ~ N(1, 1), are the following random variables also Gaussian? If so, what are their means and (co)-variances? Note that T is a vector. 3.3.1 Y = U +V O Y is not Gaussian. O Y is Gaussian. Mean is 0 and variance is 2. O Y is Gaussian. Mean is 0 and variance is 1. O Y is Gaussian. Mean is 2 and variance is 2. 3.3.2 Z = Ux V O Z is not Gaussian. O Z is Gaussian. Mean is -1 and variance is 1. O Z is Gaussian. Mean is 0 and variance is 1. O Z is Gaussian. Mean is 0 and variance is 2.So far we have learned the Gaussian elimination with naive pivoting and the Gaussian elimination with partial pivoting. In Section 4.3, the Gaussian elimination with scaled partial pivoting is introduced. Please compare these three methods. What is the difference between the Gaussian elimination with scaled partial pivoting and the Gaussian elimination with partial pivoting? The Matlab code for Gaussian elimination with scaled partial pivoting is given onQuestion 20 1 pts Let P be the transition matrix of a Markov chain with n states. Which one of the following statements is not always true? If Q is another transition matrix of a Markov chain with n states, then =(P + Q) is the transition matrix of a Markov chain with n states. O P2 is the transition matrix of a Markov chain with n states. If P is invertible, then p-1 is the transition matrix of a Markov chain with n states. If Q is another transition matrix of a Markov chain with n states, then PQ is the transition matrix of a Markov chain with n states.16) What is the Gaussian curvature of the following airfoil scheme upper surface? a) Zero Gaussian curvature b) Non-zero Gaussian curvature PT PB c) Infinite Gaussian Curvature