the dexes calculated for (2019-2020) and the Regression Model parameters are given as follows: Seasons SI Regression Model Q1 0.654 b0=12.25 Q2 1.982 bl=-0.27 0.762 Q3 Q4 The Adjusted Forecast for Q4- 2021 is: 1.596 diusted 8011 506=14 38
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Q: A researcher interested in explaining the level of foreign reserves for the country of Barbados…
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Q: A researcher interested in explaining the level of foreign reserves for the country of Barbados…
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Q: A researcher interested in explaining the level of foreign reserves for the country of Barbados…
A: From the given outputThe regression equation is FR= 5491.38 + 85.39OIL - -377.08EXP -396.99FDIa)…
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- Explain, If the population regression function changes over time, then OLS estimates neglecting this instability are unreliable for statistical inference or forecasting.?Explain the concept of Asymptotic Distribution of the OLS Estimatorand t-Statistic in the multi regression model?How can we use Eviews to tell if a regression suffers from first order autocorrelation and what are the consequences of autocorrelation on the OLS estimator?
- my question is: when there is a best fit linear regression model for a Adidas set, and we wish to use it to make an estimation describe the difference between interpolation and extrapolation. Which between interpolation and extrapolation is more likely to give a more accurate estimation?If the error term in a linear regression model is normally distributed, then the distribution of the OLS estimator, conditional on explanatory variables, is also normal. True or False, why?A funding agency has performed an internal study in which the number of loan requests (Y variable, in thousands) is related with the interest rate in percentage terms (X variable) applied to these loans. The following information is known: the mean of x= 5, the mean of y = 20000, the standard deviation of x = 1.5, the standard deviation of y = 5000 and the covariance of x and y = -5400. First, obtain the regression line that allows to estimate the number of loan requests (Y) as a function of its interest rate in percentage terms (X). Interpret the value of the obtained coefficients. Then, obtain an appropriate indicator of the goodness of fit of this model and discuss the result. Regarding the variability, obtain the explained and the error components of the variance. Interpret all the results Finally, Estimate the number of loans requests we can expect with an interest rate of 3.5%. Analyze the reliability of this prediction. What is the needed assumption to perform this prediction?
- Remove the outlier and compute the least-square regression line for predicting the president's age from the first lady's age. Round the slope and y-intercept values to at least four decimal places.The table given below indicates Small Holding Ltd.’s quarterly profits in 2019 and2020.Time Period Profit (Thousands Of Rands)2019 Q12019 Q22019 Q32019 Q42020 Q12020 Q22020 Q32020 Q4250210165195265218178204Q.6.3.1 Determine the trend regression function for this data set. In order toobtain full marks for this question, you must complete the relevanttable (template provided below) and then apply the appropriate timeseries formulae in the formulae sheet.A convenience store recently started to carry a new brand of soft drink. Management is interested in estimating future sales volume to determine whether it should continue to carry the new brand or replace it with another brand. The following table provides the number of cans sold per week. Use both the trend projection with regression and the exponential smoothing (let α=0.4 with an initial forecast for week 1 of 581) methods to forecast demand for week 13. Compare these methods by using the mean absolute deviation and mean absolute percent error performance criteria. Does your analysis suggest that sales are trending and if so, by how much? Period 1 2 3 4 5 6 7 8 9 10 11 12 Sales 581 623 640 731 668 613 759 696 763 724 659 759 Part 2 (i) Obtain the trend…
- A convenience store recently started to carry a new brand of soft drink. Management is interested in estimating future sales volume to determine whether it should continue to carry the new brand or replace it with another brand. The table below provides the number of cans sold per week. Use both the trend projection with regression and the exponential smoothing (let α = 0.4 with an initial forecast for week 1 of 617) methods to forecast demand for week 13. Compare these methods by using the mean absolute deviation and mean absolute percent error performance criteria. Does your analysis suggest that sales are trending and if so, by how much? Week 1 2 3 4 5 6 7 8 9 10 11 12 Sales 617 617 648 739 659 623 742 704 724 715 668 740Explain Consistency and Asymptotic Normality of the OLS Estimators?So I generated this table with stat program, which is from a regression of temperature (in °C) on atmospheric concentrationof carbon dioxide (CO2), in ppm. Can you please construct a 95% confidence interval for the slope of the regression equation? Also, what are the chances of seeing a linear relationship at least as strong as observed from these data, when in fact there was none in the population? What would be the conclusion from this regression?