The United Nations has hired you as a consultant to help identify factors that predict manufacturing
countries.csv
| manufacture | agriculture | exports | inflation | |||||||||||
| 1.3 | 3.4 | -2.7 | 13 | SUMMARY OUTPUT | ||||||||||
| 1 | 1.4 | -6 | 10.5 | |||||||||||
| 0.4 | 0.1 | -3.6 | 15.9 | Regression Statistics | ||||||||||
| 4.9 | 1.8 | 13.6 | 3.2 | Multiple R | 0.6268 | |||||||||
| 9.8 | 5.6 | 27.3 | 5.4 | R Square | 0.3929 | |||||||||
| -2.1 | 2.2 | 2.6 | 5.2 | Adjusted R Square | 0.3515 | |||||||||
| 2 | 2.3 | -9.5 | 8.7 | Standard Error | 3.6243 | |||||||||
| 5.8 | 3 | 4.4 | 1.4 | Observations | 48 | |||||||||
| 5.2 | 2.9 | 9.2 | 3 | |||||||||||
| -1.1 | -2.3 | -6.3 | 14.9 | ANOVA | ||||||||||
| 0.2 | 0.3 | 12 | 20.3 | df | SS | MS | F | Significance F | ||||||
| 1.1 | 1.4 | -7.2 | 19.8 | Regression | 3 | 373.9798 | 124.6599 | 9.4902 | 0.0001 | |||||
| -12 | 4.8 | -5.5 | 8.6 | Residual | 44 | 577.9669 | 13.1356 | |||||||
| -1.6 | -0.4 | -2.5 | 11.3 | Total | 47 | 951.9467 | ||||||||
| 2.9 | -0.6 | 5.4 | 7.5 | |||||||||||
| 0.5 | 1.9 | 1.6 | 19 | Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% | |||
| 2.2 | -3.5 | 4.7 | 1.9 | Intercept | 2.1505 | 0.9695 | 2.2182 | 0.0317 | 0.1966 | 4.1043 | 0.1966 | 4.1043 | ||
| 8 | 3.1 | 19.9 | 37.3 | agriculture | 0.4934 | 0.2020 | 2.4426 | 0.0187 | 0.0863 | 0.9004 | 0.0863 | 0.9004 | ||
| 6.5 | 3.3 | -0.6 | 8.9 | exports | 0.2699 | 0.0649 | 4.1564 | 0.0001 | 0.1390 | 0.4008 | 0.1390 | 0.4008 | ||
| 0.2 | 0.1 | 8.4 | 29.5 | inflation | -0.1171 | 0.0520 | -2.2499 | 0.0295 | -0.2220 | -0.0122 | -0.2220 | -0.0122 | ||
| 7.8 | 5.3 | 10.4 | 8.1 | |||||||||||
| 2.5 | 2.3 | 4.9 | 22.6 | |||||||||||
| -0.2 | 3.1 | 7.9 | 20.2 | |||||||||||
| 6.1 | 10.3 | -19 | -1.3 | |||||||||||
| 4.1 | 2.3 | 8.7 | 9.5 | |||||||||||
| -5 | 1.2 | -2 | 1.1 | |||||||||||
| 2.1 | 2.7 | 5.6 | 11.2 | |||||||||||
| 7.7 | 3 | 2 | 8.9 | |||||||||||
| 9.3 | 3.3 | 6.2 | 7.5 | |||||||||||
| -1.7 | 2 | -1.7 | 18.2 | |||||||||||
| 5.8 | 4.7 | -0.2 | 2.1 | |||||||||||
| 3.9 | -3.9 | -2.5 | 3.4 | |||||||||||
| 5.6 | 3.9 | 6.4 | 13.9 | |||||||||||
| 6.9 | 1.3 | 11.6 | 6.4 | |||||||||||
| -4.6 | 0.8 | -9.8 | 21.5 | |||||||||||
| -2.6 | 1.7 | -6.6 | 6.7 | |||||||||||
| 1.1 | 3.9 | 3.8 | 7.7 | |||||||||||
| 4.6 | 3 | -3.5 | 8.6 | |||||||||||
| -3.4 | 7.9 | -7.9 | 45.4 | |||||||||||
| -0.6 | 2.5 | 2 | 11.5 | |||||||||||
| 8.2 | 1.9 | 3.8 | 7.8 | |||||||||||
| 4.1 | 0.9 | 1.3 | 5.6 | |||||||||||
| 12.6 | 7.9 | 11.7 | 3.8 | |||||||||||
| 4.1 | 2.8 | -0.9 | 9.9 | |||||||||||
| 0.6 | 2.8 | -2.1 | 23.3 | |||||||||||
| 2 | 0.5 | -3.1 | 33.5 | |||||||||||
| 0 | 0.4 | 6.9 | 32.6 | |||||||||||
| -2.6 | -1.3 | 3.4 | 7.7 |
Question.docx
The United Nations has hired you as a consultant to help identify factors that predict manufacturing
growth in developing countries. You have decided to use multiple regression to develop a model and
identify important variables that predict manufacturing growth.
You are given a data file, ”countries.csv”, from 48 countries. The variables included are percentage
manufacturing growth (Y ), percentage agricultural growth (X1), percentage exports growth (X2), and percentage rate of inflation (X3) in 48 developing countries. Develop the multiple regression model and WRITE a report on your findings.
Hint: your analysis should include t-tests, analysis of variance (ANOVA), and
some graphs. It is also important that your report incorporates all the essential analysis and ends with a
summarizing paragraph.