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1) When looking at regression results, how do you know which of the estimated regression slope coefficients are STATISTICALLY SIGNIFICANT?
2) How do you know if the independent variables explain a large fraction of the variance when looking at regression results?
3) How can you tell by looking at regression results if a model specification suffers from SERIOUS MULTICOLINEARITY?
Evaluate the overall explanatory power of the regression model. Use a 0 . 05 level of significance. State all your hypotheses and explain your results. Do not use rules of thumb.
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A fashion firm manufactures outfits using two inputs, design skills (L) and expensive materials (M). The cost of fabrication is small and might be ignored as a first approximation.
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