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Problem 2: A government researcher is analyzing the relationship between retail sales and the gross national product (GNP).He also wonders whether there are significant differences
Problem 2: A government researcher is analyzing the relationship between retail sales and the gross national product (GNP).He also wonders whether there are significant differences in retail sales related to the quarters of the year, compared to the baseline of Q4. He collects ten years of quarterly data.
Year | Quarter | Retail sales (in millions) | GNP (in billions) |
2002 | Q1 | 696048 | 9740.5 |
2002 | Q2 | 753211 | 9983.5 |
2002 | Q3 | 746875 | 10048.0 |
2002 | Q4 | 792622 | 10184.9 |
2003 | Q1 | 704757 | 10206.2 |
2003 | Q2 | 779011 | 10350.9 |
2003 | Q3 | 756128 | 10332.2 |
2003 | Q4 | 827829 | 10463.1 |
2004 | Q1 | 717302 | 10549.7 |
2004 | Q2 | 790486 | 10634.7 |
2004 | Q3 | 792657 | 10749.1 |
2004 | Q4 | 833877 | 10832.2 |
2005 | Q1 | 741233 | 10940.2 |
2005 | Q2 | 819940 | 11073.6 |
2005 | Q3 | 831222 | 11321.2 |
2005 | Q4 | 875437 | 11508.3 |
2006 | Q1 | 795916 | 11707.8 |
2006 | Q2 | 871970 | 11864.2 |
2006 | Q3 | 873695 | 12047.3 |
2006 | Q4 | 938213 | 12216.6 |
2007 | Q1 | 836952 | 12486.3 |
2007 | Q2 | 932713 | 12613.0 |
2007 | Q3 | 940880 | 12848.7 |
2007 | Q4 | 987085 | 12994.1 |
2008 | Q1 | 897180 | 13264.0 |
2008 | Q2 | 987406 | 13423.3 |
2008 | Q3 | 978211 | 13514.8 |
2008 | Q4 | 1018775 | 13683.2 |
2009 | Q1 | 923997 | 13859.8 |
2009 | Q2 | 1016136 | 14087.6 |
2009 | Q3 | 1002312 | 14302.9 |
2009 | Q4 | 1062803 | 14489.9 |
2010 | Q1 | 953358 | 14520.7 |
2010 | Q2 | 1032919 | 14647.3 |
2010 | Q3 | 1006551 | 14689.2 |
2010 | Q4 | 966329 | 14317.2 |
2011 | Q1 | 839625 | 14172.2 |
2011 | Q2 | 919646 | 14164.2 |
2011 | Q3 | 926265 | 14281.9 |
2011 | Q4 | 985649 | 14442.8 |
- Load this data however you wish into R.
- Which variable is the response ?
- Since the researcher is interested in whether or not the Quarter of the year has an impact on retail sales, write R commands to create the dummy variables you need to recode the "Quarter" column, using Q4 as baseline.
- Using R, find the best MLR model for the data (disregard Year variable). Is the overall model significant? Justify with ANOVA hypotheses and p-value. Are the individual variables significant? If not, remove the insignificant variables stepwise, until all remaining variables are significant
- Predict retail sales in quarter 1 if GNP equals $13,000,000,000,000 (13,000 billion)
- Interpret the meaning of all significant slope coefficients in the "reduced" model.
- Look at the residual plots. Are there any patterns? Should we worry about the assumption of MLR?
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