Math Problem Statement
ewLP06dDEemJ1w4LYV5qDg_b5c9ef3e62c440eca861a856beee21c0_Week4QuizProblems_7.15.19_ (5).pdf
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Question 1 Please download the Week 4 Quiz Problems PDF attached here.
Please do not use fractions in calculations or answers; use decimals instead.
Input your solution to problem 1 here.
What is the overall proportion (across strata) of the population that has the characteristic of interest?
(At least 1 decimal digit of precision; credit awarded for answers within 0.05 of correct value.)
1 point Enter answer here 2. Question 2 What is the sampling variance of the mean from the proportionately allocated sample of n = 30?
(Hint: W = 100 / 600 = 0.16667, and (W) = (0.16667) = 0.027778. Hence, for stratum 1, where v(p) = 0.038, the contribution to the sum is (0.027778)(0.038) = 0.0010556.)
(At least 4 decimal digits of precision; credit awarded for answers within 0.0001 of correct value.)
1 point Enter answer here 3. Question 3 What is the simple random sampling variance of the estimated proportion?
(Hint: The sample size n = 30, sampling fraction is f = n / N = 30 / 600 = 0.05, and = 0.24.)
(4 decimal digits of precision; credit awarded for answers within 0.0005 of correct value.)
1 point Enter answer here 4. Question 4 What is the gain in precision from using proportionately allocated stratified sampling?
(At least 3 decimal digits of precision; credit awarded for answers within 0.001 of correct value.)
1 point Enter answer here 5. Question 5 What is the sampling variance of the mean from the entire “equal allocation” sample of n = 30?
(At least 4 decimal digits of precision; credit awarded for answers within 0.0001 of correct value.)
1 point Enter answer here 6. Question 6 What is the design effect from using “equal allocation” stratified sampling?
(At least 4 decimal digits of precision; credit awarded for answers within 0.001 of correct value.)
1 point
Solution
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Math Problem Analysis
Mathematical Concepts
Stratified Sampling
Variance
Proportionate Allocation
Simple Random Sampling
Design Effect
Formulas
Overall Proportion: P_w = ∑(W_h * P_h)
Sampling Variance (proportionate allocation): v(p_w) = ∑(W_h^2 * v(p_h))
Random Sampling Variance: v(p_0) = (1 - f) * S^2 / n
Gain in Precision: 1 - deff = 1 - v(p_w) / v(p_0)
Design Effect: deff = v(p_w) / v(p_0)
Theorems
Central Limit Theorem
Law of Large Numbers
Suitable Grade Level
Undergraduate Statistics
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