Consider the following quarterly time series.Quarter1234Year1923Year21,1121,056 1,156992Year31,0781,2431,124 1,124 1,2541,3011,198a. Construct a time series plot. What type of pattern exists in the data?b. Use a multiple regression model with dummy variables as follows to develop an equation to account for seasonaleffects in the data. Qtr1 = 1 if quarter 1, 0 otherwise; Qtr2 = 1 if quarter 2, 0 otherwise; Qtr3 = 1 if quarter 3, 0 otherwise.c. Compute the quarterly forecasts for next year based on the model developed in part b.

Given Information:Consider the given data:QuarterYear 1Year 2Year…

Answered: sider the following quarterly time…

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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You generate a scatter plot using Excel. You then have Excel plot the trend line and report the equation and the r2r2 value. The regression equation is reported asy=60.71x+33.51y=60.71x+33.51and the r2=0.1764r2=0.1764.What is the correlation coefficient for this data set?r =
Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (Each pair of variables has a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The caloric content and the sodium content (in milligrams) for 6 beef hot dogs are shown in the table below. Calories, x 130 130 350 370 150 (a) x 160 calories (b)x= 100 calories Sodlum, y (c) x 140 calories (d) x=200 calories Find the regression equation. (Round to three decimal places as needed.) Choose the correct graph below. OA 560 Q Q 200 G Calories (a) Predict the value of y for x = 160. Choose the correct answer below. OA. 393.094 OB. 440.954 OC. 536.674 OD. not meaningful (b) Predict the value of y for x= 100. Choose the correct answer below. OA 297.374 OB. 536.674 OC. 393.094 OD. not meaningful (c) Predict the value of y for x = 140. Choose the correct answer below. OA 297.374 OB.…
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Graph the scatterplot and find the equation of the regression line GDP. CO2 emissions (in millions metric tons) 1.7. 552.6 1.2. 462.3 2.5. 475.4 2.8. 374.3 3.6. 748.5 2.2. 400.9 0.8. 253.0 1.5. 318.6 2.4. 496.8 5.9. 1180.6
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b. Add in the table provided in the spreadsheet a dummy variable that takes the value of 1in the fourth quarter of each year and show the table with all the data c. Using the data provided in the spreadsheet including the dummy variable you have created for the fourth quarter of each year run a regression with dependent variable the CBC house price index and independent variables the other three variables (Nominal GDP, Number of Households, and the dummy variable for the fourth quarter). Present the typical regression results output for this regression produced by Excel. d. Explain what the particular numbers for the following statistics that you presented in b) mean (no points will be given if you write general definitions without interpreting the particular numbers that you have presented): a. R-squared b. The t-statistics of the three independent variables c. The coefficients of the three independent variables e. Discuss if the signs that you get for the coefficients of each of the…
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Use the regression equation to predict the value of y for x = -1.6. Assume that the variables x and y have a significant correlation. -5-34 1 -1-2 X 0 2 3 -4 y - -10 8 9 1 -2-6 -1 3 6 -8 OA. 1.214 OB. -2.803 O C. 2.980 OD. -3.907
Use R programming or excel to answer the following. Visualize your answers. Consider the following quarterly time series: Quarter Year 1 Year 2 Year 3 1 923 1112 1243 2 1056 1156 1301 3 1124 1124 1254 4 992 1078 1198 Construct a time series plot. What type of pattern exists in the data? Use a multiple regression model with dummy variables as follows to develop an equation to account for seasonal effects in the data. Qtr1 = 1 if quarter 1, 0 otherwise; Qtr2 = 1 if quarter 2, 0 otherwise; Qtr3 = 1 if quarter 3, 0 otherwise. Compute the quarterly forecasts for next year based on the model developed in part b.

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