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Explanation of Solution
The formulas for sum of squares are as follows:
The total sum of squares is calculated is as follows:
Consider
Thus, the required TSS is as follows:
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Chapter 13 Solutions
Mathematical Statistics with Applications
- Find the variance by calculating the first two moments of the random variable X = (- 1 / λ) ln (1-U), where U ~ U (0,1) and λ> 0.arrow_forwardConsider a real random variable X with zero mean and variance σ2X . Suppose that wecannot directly observe X, but instead we can observe Yt := X + Wt, t ∈ [0, T ], where T > 0 and{Wt : t ∈ R} is a WSS process with zero mean and correlation function RW , uncorrelated with X.Further suppose that we use the following linear estimator to estimate X based on {Yt : t ∈ [0, T ]}:ˆXT =Z T0h(T − θ)Yθ dθ,i.e., we pass the process {Yt} through a causal LTI filter with impulse response h and sample theoutput at time T . We wish to design h to minimize the mean-squared error of the estimate.a. Use the orthogonality principle to write down a necessary and sufficient condition for theoptimal h. (The condition involves h, T , X, {Yt : t ∈ [0, T ]}, ˆXT , etc.)b. Use part a to derive a condition involving the optimal h that has the following form: for allτ ∈ [0, T ],a =Z T0h(θ)(b + c(τ − θ)) dθ,where a and b are constants and c is some function. (You must find a, b, and c in terms ofthe information…arrow_forwardLet X1, X2, . . . , Xn be an i.i.d. random sample from a Beta distribution with density: f(x; θ) = Γ(2θ) Γ(θ) 2 x θ−1 (1 − x) θ−1 , 0 < x < 1, θ > 0. Find a sufficient statisticarrow_forward
- Let X1, X2 be two independent random variables with the same mean EXi = µ andpossibly different variances Var(Xi) = σ2i (sigma squared i), i = 1, 2. Consider the weighted average Y =λX1 + (1 − λ)X2 where λ is a constant.(a) Compute EY and Var(Y )(b) Find the λ in terms of σ2i (sigma squared i) , i = 1, 2 that minimizes Var(Y ).arrow_forwardLet X and Y be two random variables with joint probability mass function: p(x,y) = 1/48 xy(1+y) ??? x=1,2,3 ??? y=1,2 p(x,y) = 0, Otherwise. Please enter the answer to 2 decimal places. What is the variance if (4-2X)?arrow_forwardA random sample of size n = 4 taken from a normal population with σ2 = 9 is used to test H0 : µ = µ0against H1 : µ = µ1 where µ1 > µ0. e null hypothesis will be rejected if X > µ ¯0 + 2.5. Find the levelof significance of the critical regionarrow_forward
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