Use WEO data You will see "data for the final " there are 3 variables: Inflation (dependent) and two independents: Peruvian Fish Price, and Poultry from Georgia's Price Find the correlation between (Inflation vs Fish) and (Inflation vs Poultry) Present the regression.Present the equation of the regression Use the information of the regression and correlation of the data - use the information about patterns of bivariate / multivariate relationship and explain the relationship. Which variables are suppressor, noncontributing and so on. Please answer these questions using these results. I used excel to get the data but I don't know how to explain it SUMMAR+E8:M81Y OUTPUT Regression Statistics Multiple R 0.5928 R Square 0.3514 35.14% Poultry Correlation Purvian Fish Correlation -0.5780249 -0.5146074 Adjusted R Square 0.3232 Standard Error 7.4409 Observations 49 ANOVA df SS MS F Regression 2 1379.6591 Residual 46 2546.8606 689.8295505 12.4593232 55.36653478 Significance F 4.7418E-05 Total 48 3926.5197 Coefficients Standard Error t Stat Intercept PERUVIAN FISH PRI POULTRY 22.14143549 2.72166544 -0.008962193 0.00361746 -0.040355644 0.03647918 P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% 8.135252463 1.8701E-10 16.6630071 27.6198639 16.6630071 27.6198639 -2.477481498 0.0169657 -0.0162438 -0.0016806 -0.0162438 -0.0016806 -1.106265209 0.27436381 -0.1137844 0.03307313 -0.1137844 0.03307313
Use WEO data You will see "data for the final " there are 3 variables: Inflation (dependent) and two independents: Peruvian Fish Price, and Poultry from Georgia's Price Find the correlation between (Inflation vs Fish) and (Inflation vs Poultry) Present the regression.Present the equation of the regression Use the information of the regression and correlation of the data - use the information about patterns of bivariate / multivariate relationship and explain the relationship. Which variables are suppressor, noncontributing and so on. Please answer these questions using these results. I used excel to get the data but I don't know how to explain it SUMMAR+E8:M81Y OUTPUT Regression Statistics Multiple R 0.5928 R Square 0.3514 35.14% Poultry Correlation Purvian Fish Correlation -0.5780249 -0.5146074 Adjusted R Square 0.3232 Standard Error 7.4409 Observations 49 ANOVA df SS MS F Regression 2 1379.6591 Residual 46 2546.8606 689.8295505 12.4593232 55.36653478 Significance F 4.7418E-05 Total 48 3926.5197 Coefficients Standard Error t Stat Intercept PERUVIAN FISH PRI POULTRY 22.14143549 2.72166544 -0.008962193 0.00361746 -0.040355644 0.03647918 P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% 8.135252463 1.8701E-10 16.6630071 27.6198639 16.6630071 27.6198639 -2.477481498 0.0169657 -0.0162438 -0.0016806 -0.0162438 -0.0016806 -1.106265209 0.27436381 -0.1137844 0.03307313 -0.1137844 0.03307313
Chapter1: Making Economics Decisions
Section: Chapter Questions
Problem 1QTC
Related questions
Question
Transcribed Image Text:Use WEO data You will see "data for the final " there are 3 variables: Inflation (dependent) and two independents:
Peruvian Fish Price, and Poultry from Georgia's Price Find the correlation between (Inflation vs Fish) and (Inflation
vs Poultry) Present the regression.Present the equation of the regression Use the information of the regression and
correlation of the data - use the information about patterns of bivariate / multivariate relationship and explain the
relationship. Which variables are suppressor, noncontributing and so on. Please answer these questions using these
results. I used excel to get the data but I don't know how to explain it
SUMMAR+E8:M81Y OUTPUT
Regression Statistics
Multiple R
0.5928
R Square
0.3514
35.14% Poultry Correlation
Purvian Fish Correlation -0.5780249
-0.5146074
Adjusted R Square
0.3232
Standard Error
7.4409
Observations
49
ANOVA
df
SS
MS
F
Regression
2
1379.6591
Residual
46 2546.8606
689.8295505 12.4593232
55.36653478
Significance F
4.7418E-05
Total
48 3926.5197
Coefficients Standard Error
t Stat
Intercept
PERUVIAN FISH PRI
POULTRY
22.14143549 2.72166544
-0.008962193 0.00361746
-0.040355644 0.03647918
P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
8.135252463 1.8701E-10 16.6630071 27.6198639 16.6630071 27.6198639
-2.477481498 0.0169657 -0.0162438 -0.0016806 -0.0162438 -0.0016806
-1.106265209 0.27436381 -0.1137844 0.03307313 -0.1137844 0.03307313
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