Suppose we observe two independent random samples X1,..., X, with each X; ~ N(u1, 0²) and Y1,...,Yng with each Y; ~ N(42, o²).We will assume that µ1, #2 and o² are unknown.We are given z = 10.1, ỹ = 7.1, s = 5.5 and s? = 6.4, with ny = 13 and ng = 19.Suppose we want to formally test the assumption tha: the variances of the the two populations the samples come from are equal. What is thetest statistic we should use?Select one:O a. W("1 1)53%3D2~6.4O b. F%3DO c. W(n-1)s2.5.5We will now compute a 95% contidence interval tor the ratio ot . Here, we are no longer assuming equal variances, so o denotes thepopulation variance of each X; and of denotes the population variance of each Y;.What is the lower endpoint of this confidence interval? Give answer to 3 decimal places.What is the upper endpoint of this confidence interval?

We want to find 95% CI for ratio of population variances

Answered: Suppose we observe two independent…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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6. An optical device is used to detect the passage of cars in a single lane of a downtown street. Because there must be at least half a second between successive cars, it is assumed that the times T; between = 0.50 + Si, where S1, S2, ··. are independent exponential (A) random cars are of the form T; variables. (a) Find the mean and variance of each T;. (b) Let Y, be the time at which the nth car passes the detector. Calculate the mean and variance of Yn. (c) Under what conditions is Yn approximately normally distributed and why? (d) When n = 50 and A = 0.10, calculate the approximate probability that Yn exceeds 500 seconds.
4) A set of measurements is given as follows. X = [0.1, 0.3, 0.8, 12,4, 7,9] We want to approximate the source of this data with Gamma distribution, i.e., X~Gamma(a, B). For Gamma distribution, the mean and variance can be found from the below equations. a Hx a o = Find the parameters of Gamma distribution to fit the data. Come up with two other distributions that you think are good representation of this data. Justify your answer.
answer item 4 only
k = Question 5 Suppose the random variables X and Y have a pdf given by f (x, y) = x+y on 0 Y). prob = b. Find F (,글): ans = Question 6 ch 30 Hisense
A random sample X1, X2, ..., Xn is obtained for a random variable X believed to be distributed as Beta(a, 7) (notice that B = 7 is known). Use the method of moments to determine the value of given 0.72.
9. (8') Let X,, X,, X, be a sample of size n=3 from a distribution with unknown mean u, -0 < u<0, where the variance o is a known positive number. Show that both à =i and ê, = 2X, + X, +5X, are unbiased estimators for H.
7. Suppose a teacher looks at a random sample of 42 final exam completion times and finds a mean timeof 111 minutes with asamplestandard deviation of 44 minutes. Which equation should they use tocompute the margin of error?A.E=s√nB.E=z√pqnC.E=zs√nD.E=ts√nE.E=t√pqn 8. Suppose a teacher looks at a random sample of 42 final exam completion times and finds a mean timeof 111 minutes with asamplestandard deviation of 44 minutes. Which value best approximates themargin of error for a 95% confidence interval?A.E= 6.8B.E= 33.4C.E= 13.3D.E= 13.7E.E= 34.4 9. A TWISTER spinner has four outcomes; red, blue, yellow, green. Tim believes that the proportion ofred outcomes is not equal to 25%. Which of the following correctly depicts hisnull hypothesis,H0?A.H0:μ >25B.H0:μ= 25C.H0:μ <25D.H0:μ6= 25E.H0:p=.25F.H0:p > .25G.H0:p < .25H.H0:p6=.25Page 2 10. A TWISTER spinner has four outcomes; red, blue, yellow, green. Tonya tests the claim that theproportion of red…
Consider the one-way analysis of variance model Xij = µ + a; + Eij, i= 1,.., m, j= 1,..., ni, where ɛij ~ N(0,0²) are independent. Let n= n1 + · ·+ nm, ... ni 1 ni 1 X;. >Xii for i = 1,..., m, and X. = - ΣΣΧ. ni j=1 i=1 j=1 (a) Show that SS(TO) = SS(T) + SS(E), where SS(TO) = E E i=12j=1 (Xij – X..)², m m ni SS(T) Σι (X.-Χ.) and SS(E) -ΣΣ (Χ- X.) . i=1 i=1 j=1
Let X~Geo(0.3). Find the following a. P(X = k). b. P(1 ≤ X 3) and describe its interpretation. d. The mean μ = E(X) and the Variance σ2 = Var (X) of the random variable X.
The following table consists of one student athlete's time, x, (in minutes) to swim 2,500 yards and the student's heart rate, y, (beats per minute) after swimming on a random sample of 5 days: Athlete's Time (x) Heart Rate (y) x2 y? ху 33.43 145 34.89 150 35.12 125 37.27 143 36.56 138 ТОTAL 1. Compute for the value of Pearson's r. 2. Interpret the value of r.
3.4 Solve the below problem: Let Y, and Y, have a bivariate normal distribution: 2. 1. 2. Y2-H2 exp 2no,02y1-p2 2(1-p2) {. (ज-र.) + ( ज-र) (ज-पदर) 07 (जब)} Dr= –00 < y, < ∞, -00 < y2 < ∞, Show that the marginal distribution of Y, is normal with mean µz and variance o is given by: 2, 1 f(y2) = 203 ,-00 < Y2 < ∞ 2.
n,T 3. Suppose {uit}i=1,t=1 be i.i.d. variables with mean zero and variance o?. Show that for each i, Auit is autocorrelated. That is, Auit is correlated to some of its past values. E.g., it is enough to calculate Cov (Auit, Auit-1) and Cov (Auit, Auit-2) to see if any of these are non-zero.

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