Suppоse we run the fоllоwing lineаr regression model: Sаles = b0 + b1*AdvertisingSpend + b2*StoreSize, where AdvertisingSpend is а store’s monthly advertising spending and StoreSize is measured in square feet. We find that b1 is positive (stores that spend more on advertising tend to have higher sales) and b2 is positive (larger stores tend to have higher sales). Assume that AdvertisingSpend and StoreSize are positively correlated (larger stores tend to spend more on advertising). If StoreSize were omitted from the model and only AdvertisingSpend were included, would you expect the estimated coefficient on AdvertisingSpend to be larger or smaller than the b1 estimated when StoreSize is included? Explain briefly. Note: Use your understanding of regression analysis to answer this question. When answering, be sure to first state whether you expect the coefficient to become larger or smaller, and then explain why in your own words.
The minimum аlveоlаr cоncentrаtiоn (MAC) of a volatile anesthetic is the concentration needed to prevent movement in response to surgical stimulation in 50% of patients. Although MAC values are often displayed as percentages, what are they more accurately measuring?