Given a two-factor factorial experiment and the ANOVA summary table that follows, fill in all the missing results. МeanDegrees ofSum ofSquareSquares (Variance)SourceFreedomFAr - 1 = 2SSA = ?MSA = 80 FSTAT=?Bc -1 = ?SSB =220 MSB= ? FsTAT = 11.0%3!AB(r - 1)(c - 1) = 8 SSAB = ? MSABrc(n' – 1) = 30n - 1 = ?= 10 FSTAT = ?ErrorSSE = ?MSE = ?TotalSST = ?

Given: Degrees of freedom ( df) for A =2 df of AB=8 df of error =30 SSB=220 MSA=80 MSAB=10 FSTAT…

Answered: Given a two-factor factorial experiment…

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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Question # 20. Two college instructors are interested in whether or not there is any variation in the way they grade math exams. They each grade the same set of 30 exams. The first instructor’s grades have a variance of 52.3. The second instructor’s grades have a variance of 89.9. Test the claim that the first instructor’s variance is smaller. (In most colleges, it is desirable for the variances of exam grades to be nearly the same among instructors.) The level of significance is 10%.
In testing the lethal concentration of a chemical found in polluted water, it is found that a certain concentration will kill 20% of the fish that are subjected to it for 24 hours. If 20 fish are placed in a tank containing this concentration of the chemical, a) find the number expected to survive out of 20 b) Find the variance of the number of survivors out of 20.
An analysis of variance produces SSb = 30, SSw = 60, F-ratio with df = 2, 15. For this analysis, what is the F-ratio?
Suppose X has finite variance. Let Y = |X|. Does Y have the same, a smaller, or a larger variance than X? Justify your answer.
The assumption of homogeneity of variance is met when _.1.the variance is the same as the interquartile range2.the variance in different groups is significantly different3.the variance across groups is proportional to the means of those groups4.the variance in different groups is approximately equal
1. You plan to use a rod to lay out a square, each side of which is the length of the rod. The length of the rod is μ, which is unknown. You are interested in estimating the area of the square, which is μ^2. Because μ is unknown, you measure it n times, obtaining observations X1, X2,..., Xn. Suppose that each measurement is unbiased for μ with variance σ^2. a. Is X^2 a biased or an unbiased estimate of the area of the square? b. Find an unbiased estimate of the area of the square.
A population of N = 5 scores has a variance of σ 2 = 24. If the scores were from a sample, what value would be obtained for the sample variance?
An analysis of variance produce SStotal=100 and SSwithintreatments=40. For this analysis, what is SSbetweentreatments? a)50 b)60 c)140 d)cannot be determined without additional information
Q3 - Returns on stocks X and Y are listed below: Period 1 2 3 4 5 6 7Stock X 3% -2% 9% 6% -1% -4% 11%Stock Y 1% -4% 7% 12% 3% -2% -1% Consider a portfolio of 20% stock X and 80% stock Y. What is the (population) variance of portfolio returns? Please round your answer to six decimal places.
Q3 - Returns on stocks X and Y are listed below: Period 1 2 3 4 5 6 7Stock X 5% 6% -2% -4% 6% 10% 7%Stock Y 1% -3% 6% 3% 12% 7% -5% Consider a portfolio of 40% stock X and 60% stock Y. What is the (population) variance of portfolio returns?Please round your answer to six decimal places.
No, this solution is not correct. The variance of an exponentially distributed random variable is the square of its mean, so Var(L) = (1/Y)^2. However, the given solution incorrectly multiplies this by Var(Y) to obtain an incorrect expression for Var(L). The correct approach to find Var(L) involves using the law of total variance. The law of total variance states that Var(L) = E[Var(L|Y)] + Var(E[L|Y]). We already know that Var(L|Y) = (1/Y)^2, so E[Var(L|Y)] = E[(1/Y)^2]. We also know that E[L|Y] = 1/Y, so Var(E[L|Y]) = Var(1/Y). To find E[(1/Y)^2] and Var(1/Y), we need to use the formulas for the expected value and variance of a function of a random variable. These involve integrating the function multiplied by the probability density function of the random variable. Once we correctly compute E[(1/Y)^2] and Var(1/Y), we can plug the correct values into the law of total variance to find the correct value for Var(L).
A one-way analysis of variances produces dftotal = 39 and dfwithin = 36. For this analysis, what is dfbetween? A)1 B) 2 C) 3 D) 0

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