2) The following results are an autoregression for US Exports to Mexico where the dependent variable is the lagged value of US Exports. Based on these regression results, what is your forecast of US Exports to Mexico for March 2005? 2) The following results are an autoregression for US Exports to Mexico where thedependent variable is the lagged value of US Exports.SUMMARY OUTPUTRegression StatisticsMultiple RR SquareAdjusted RSquareStandard ErrorObservations0.5580.3110.296129948ANOVASignificancedfSS35017027MSFRegressionResidualTotal350127213.827E-054647775832151126002421686592StandardCoefficients6300Error1778t Stat3.54Upper95%9879P-valueInterceptLagged ExportsLower 95%27210.3150.00091920.5630.1244.563.827E-050.812Based on these regression results, what is your forecast of US Exports to Mexico forMarch 20057

Answered: Image /qna-images/answer/43caf540-e35c-4eda-9c4c-e36a78ae25df.jpg

The following results are an autoregression for US Exports to Mexico where the dependent variable is the lagged value of US Exports. Based on these regression results, what is your forecast of US Exports to Mexico for March 2005?

The following results are an autoregression for US Exports to Mexico where the dependent variable is the lagged value of US Exports. Based on these regression results, what is your forecast of US Exports to Mexico for March 2005?

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Similar questions

Imagine that you, a social psychologist, study people living with HIV. You are interested in the relationship between viral load, the amount of HIV in a sample of blood, and perceived stigma, the amount people with HIV perceive others to hold stigmatizing views about their condition. You have 100 people with HIV complete a perceived stigma scale, as well as provide a sample of blood, so their viral load can be measured. You run a regression analysis using the data you’ve collected to see whether perceived stigma can be predicted based on viral load. The output from the analysis is presented below: How much does the estimate of perceived stigma change if viral load increases by one unit?
Discuss how the autocorrelation would affect the regression estimates in the regression analysis.
Develop a scatterplot and explore the correlation between customer age and net sales by each type of customer (regular/promotion). Use the horizontal axis for the customer age to graph. Find the linear regression line that models the data by each type of customer. Round the rate of changes (slopes) to two decimal places and interpret them in terms of the relation between the change in age and the change in net sales. What can you conclude? Hint: Rate of Change = Vertical Change / Horizontal Change = Change in y / Change in x
Suppose you wanted to test whether or not the payoff to an additional year of education was the same for men and women in the STEM majors. How would you set up your regression analysis in this case
A researcher is studying the intensity of hurricanes that entered the Gulf of Mexico between 1975-2015 and the average water temperature of the Gulf of Mexico at the hurricane's peak strength. What is the independent and dependent variable in this study?
An online retailer examined their transactional database to see how the value of total annual purchases ($) for individual customers was related to their annual income ($). They obtained the following regression model:Total annual purchases = -49.80 + 0.0246(annual income)correlation = 0.533(a) What does the slope tell us? (Annual Income/ Total Annual Purchases) is/are predicted to increase by ($0.0246 / -$49.80) for each additional $1 of (Annual Income/ Total Annual Purchases).(b) What does the intercept tell us? A.The intercept does not have a practical meaning in this context. B. Total annual purchases are predicted to be $0.0246 when annual income = 0. C. Total annual purchases are predicted to be $-49.80 when annual income = 0. D. Annual income is predicted to be $0.0246 when total annual purchases = 0. E. Annual income is predicted to be $-49.80 when total annual purchases = 0. (c) Which statement is correct concerning the quality of this model? A. 28.4% of the variability in…
A researcher interested in explaining the level of foreign reserves for the country of Barbadosestimated the following multiple regression model using yearly data spanning the period 2001 to 2016: ??=?+????+????+????Where FR = yearly foreign reserves ($000’s), OIL = annual oil prices, EXP = yearly total exports ($000’s) and FDI = annual foreign direct investment ($000’s). The sample of data was processed using MINITAB and the following is an extract of the output obtained:Predictor Coef StDev t-ratio p-value Constant 5491.38 2508.81 2.1888 0.0491OIL 85.39 18.46 4.626 0.0006EXP -377.08 112.19 * 0.0057FDI -396.99 160.66 -2.471 ** S = 2.45 R-sq = 96.3% R-sq(adj) = 95.3%Analysis of VarianceSource DF SS MS F pRegression 3 1991.31 663.77 ? ??Error 12 77.4 6.45Total 15 Perform the F Test making sure to state the null and alternative hypothesis. f) Given an interpretation of the term “R-sq” and comment on its value.
A study of king penguins looked for a relationship between how deep the penguins dive to seek food and how long they stay underwater. For all but the shallowest dives, there is a linear relationship that is different for different penguins. The study report gives a scatterplot for one penguin titled " The relation of dive duration (DD) to depth (D)." Duration DD is measured in minutes and depth D is in meters. The report then says, " The regression equation for this bird is: DD = 2.33 + 0.001 D. (a) What is the slope of the regression line?. ANSWER ? minutes per meter. (b) According to the regression line, how long does a typical dive to a depth of 100 meters last? ANSWER ? minutes.
If the equation of the regression line that relates income in dollars of student’s parents, xx, with cost in dollars of tuition,yy, is y=8500+0.018xy=8500+0.018x. a. What is the best prediction for the tuition of students whose parents earn no income? b. What is the best prediction for the tuition of students whose parents earn $45000? c. What is the best prediction for the tuition of students whose parents earn $80000?
Describe three approaches to modeling seasonality in a regression forecast.