YEAR 1971.3 1971.4 1972.1 1972.2 1972.3 1972.4 1973.1 1973.2 1973.3 1973.4 1974.
ID: 1105437 • Letter: Y
Question
YEAR 1971.3 1971.4 1972.1 1972.2 1972.3 1972.4 1973.1 1973.2 1973.3 1973.4 1974.1 1974.2 1974.3 1974.4 1975.1 1975.2 X2 2.26 2.54 3.07 2.91 2.73 2.77 3.59 3.23 X3 3.49 2.85 4.06 3.64 3.21 3.66 3.76 3.49 3.13 X4 158.11 173.36 165.26 172.92 178.46 198.62 186.28 188.98 180.49 183.33 181.87 185 184 188.2 175.67 188 X5 11484 9348 8429 10079 9240 8862 6216 8253 8038 7476 5911 7950 6134 5868 3160 5872 4 9 2.89 3.77 3.64 2.82 2.96 4.24 3.69 10 3.65 12 2.94 3.12 3.58 3.53 13 15 16 Y- quantity of roses sold, dozens X2-average wholesale price of roses, $/dozen X3- average wholesale price of carnations, $/dozen X4- average weekly family disposable income, $/week X5= the trend variable taking values of 1, 2, and so on, for the period 1971-111 to 1975-II in the Detroit metropolitan area You are asked to consider the following demand functions: a. Estimate the parameters of the linear model and interpret the results b. Estimate the parameters of the log-linear model and interpret the resultsExplanation / Answer
a.
The equation is able to capture 91 per cent of variation as R-square is 0.91
b.
The equation is able to capture 88 per cent of variation as R-square is 0.88
General interpretation, If we increase X by one percent, we expect Y to increase by (1/100) units of Y
SUMMARY OUTPUT Regression Statistics Multiple R 0.91 R Square 0.83 Adjusted R Square 0.77 Standard Error 969.87 Observations 16.00 ANOVA df SS MS F Significance F Regression 4 52249136.4 13062284.1 13.89 0.0003 Residual 11 10347219.6 940656.327 Total 15 62596356 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 10816.04 5988.35 1.81 0.10 -2364.22 23996.31 X2 -2227.70 920.47 -2.42 0.03 -4253.64 -201.77 X3 1251.14 1157.02 1.08 0.30 -1295.44 3797.73 X4 6.28 30.62 0.21 0.84 -61.11 73.68 X5 -197.40 101.56 -1.94 0.08 -420.93 26.13Related Questions
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