In this question you will consider ergodicity and time series averages.Consider the following MA (2) time series model:Y₁ = t -0₁ €t-1 - 0₂€t-2(d) You are told that o² = 1, 0₁:=0.2 and 0₂-0.1 is the variancefor the time series mean estimator less efficient or more efficientthan the T 20 sample size ensemble average i.i.d. case?Justify your answer with a relevant calculation and explanationusing the formula in Equation (1) provided above in part (c) ofthis question.==

ANSWER: The formula for the variance of the time series mean estimator in the MA(2) model is:…

Answered: In this question you will consider…

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 2 The city of Chicago decides to understand whether its citizens consume more alcohol during the summer period. As a baseline, the average person consumes 0.7L of alcoholic beverages in each week outside the summertime. In June of a given year, they collected a simple random survey of 28 people and estimated an average per capita consumption of 0.95L per week. Moreover, they estimated a sample variance of 0.85L² a) State the null and alternative hypothesis of the test. b) Compute the relevant test statistic. Show all steps. c) The researchers conducting this assessment decide to restrict the type 1 error to 10%. Find the critical value(s) for the test and justify your answer. d) Find the p-value for the test. Explain your answer. Draw a graph with a representation of the p-value with the relevant values in the test. e) Conclude the test.
Consider the following regression model: y-Be+Bex=+Bex+Baxa+Bexetu. The sample size is N=105. Using F test, we want to test: Ho: B+B=1, B-0, 3-4 H₁: O/W. What is the number of restrictions in the null hypothesis. O 8.4 Ob.3 091 O d. 2
What happens when you overfit a regression model? Question 25 options: The model captures too much of the random variation in the sample data and fails to predict accurately for the population. The p-value for the F-test of overall significance is greater than 0.05. So many variables are added to the model that the Adjusted {"version":"1.1","math":"<math xmlns="http://www.w3.org/1998/Math/MathML"><msup><mi>R</mi><mn>2</mn></msup></math>"} value exceeds 1 None of the relationships in the model are found to be statistically significant.
8. You collect data on people's height and study the relationship between gender and height. A regression of the height on a binary variable (Female), which takes a value of one for females and zero otherwise, yields the following result: Height = 71.0- 4.84 x Female, R2 = 0.40, SER = 2.0 (0.3) (0.57) (a) What is the sample average male height? (b) What is the sample average female height? I (c) How to interpret the slope coefficient -4.84? (d) Is the error term in the regression more likely to be heteroskedastic or homoscedastic? Why? R English (United States) D'Focus Page 9 of 10 920 words 100%
Find the Q1, Q3 and IQR of the 1% hydrogen peroxide
Answer all
Question 5 of 19 Compute the MSE for the following data. Period 1 2 3 4 5 6 13 Select the correct response. 12 11 Actual 492 470 485 493 498 492 14 Forecast (Error) 495 465 487 490 499 498 -5 -3 1 6 |Error] 3 LO 5 2 3 1 6 Error² 9 25 4 9 1 36 Error/Actual*100 0.60 1.06 0.41 0.60 0.20 1.21
4. A simple linear regression is fit to a dataset. Unfortunately, the corresponding ANOVA table is not complete because some quantities in the table are missing due to unknown digital errors. Calculate the missing values, denoted by "?", in the ANOVA table based on the other available values. Is this regression model significant (α = 0.05)? Source Regression Residual Total df ? ? 21 SS ? ? ? MS = SS/df ? 1.13 F-Ratio 430.65 p-value ?
The table below lists measured amounts of redshift and the distances (billions of light-years) to randomly selected astronomical objects. Find the (a) explained variation, (b) unexplained variation, and (c) indicated prediction interval. There is sufficient evidence to support a claim of a linear correlation, so it is reasonable to use the regression equation when making predictions. For the prediction interval, use a 90% confidence level with a redshift of 0.0126. Redshift Distance 0.0238 0.31 a. Find the explained variation. 0.0543 0.74 (Round to six decimal places as needed.) b. Find the unexplained variation. (Round to six decimal places as needed.) c. Find the indicated prediction interval. 0.0722 1.02 billion light-years
2. We performed a linear regression using 25 observations. From the regression output we find that bo = 5.7, bị = 12.9, x = 11.4, Sz = 3.2 and MSE = 12.25. a. From the least squares line, what is the predicted response when x* = 10.65? y = b. What is the 95% confidence interval for the mean response when x* = 10.65? c. What is the 95% prediction interval for an individual response when x* = 10.65? d. Which interval is wider? The confidence interval or the prediction interval? O a. Confidence Interval b. Prediction Interval
QUESTION 1 Manama cement factory produces precast cement blocks, last year's record showed the mean weight per block as 21.05 KG. This year they have sampled 50 units, and the maximum acceptable weight per block was 29.85, with a variance of 13.51 KG. Calculate the z value associated with this sample? (Write your answer in 2 decimals places e.g. 0.99)
Part A of question one asks for the variance (sigma squared), not the equation of regression line. Is the variance 2.79 as I listed on my answer sheet? Maybe my image didn't go through, but I already had the answer to subparts B and C to the question, which you list as #2 and #3. But I need help with parts D, E, and F. I have the following answers for D. d. Y hat (fitted value = 426.46), with residual of -1.62. e. r squared value = 1.00 g. 99% confidence interval = (-11.63, -1.05) Thanks thanks

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