Lisa Fisher is a business school professor who would like to analyze university factors that enhance innovation. She collects data on 143 universities in 2008 for a regression where the response variable is the number of startups (Startups), which is used as a measure for innovation. Lisa believes that the amount of money that a university directs toward research (Research) is the most important factor influencing Startups. She estimates Startups as a function of Research and obtains

Two other explanatory variables are also likely to influence Startups: the number of patents issued (Patents), and the age of its technology transfer office in years (Duration). Lisa then includes these additional variables in the model and obtains

- 0.02Duration; SSE = 1,368.14; n = 143 At the 5% significance level, should Lisa include Patents and Duration in the model predicting Startups?

Transcribed Image Text:

Startups=0.21 +0.01 Research; SSE= 1.43478; n=143 Startups 0.42+0.01Research+ 0.05Patents