A new footwear manufacturer is trying to compete with the major brands by investing heavily in Research and Development (R&D). Their goal is to produce a premium lifestyle sneaker that is more comfortable, longer lasting and more stylish than any of their competitors. Below are some data on dollars spent on R&D and new customers acquired for the last 5 quarters. Regression Equation: Y=0.5+ 1.35X New Customers R&D Dollars Acquired (in millions) (in thousands) 8 12 12 15 13 18 14 20 18 25 What is the minimum amount of money, in millions, the company can forecast to spend on R&D in order to predict at least 35,000 new customers? 28 24 26 20

During the 1950's and 1960's the average weight of vehicles sold in the U.S. was well over 4,000 pounds. There was a dip in the average weights in the 1970's and 1980's, due possibly to both higher demand for better gas mileage and a world-wide shortage of crude oil. Then in the 1990's and early 2000's the average weight of vehicles had a steady increase. A regression analysis was completed on the average weight of the 10 most commonly sold vehicles in the U.S. from the years 2012 through the year 2020 and yielded the following results, where the independent variable is the year and the predicted variable is the average weight of the 10 most popular vehicles.             Correlation of "Average Weight" and "Year" = r = 0.9283             The regression equation is "Average Weight"  =  –124,960.73 + 63.82(Year)   Predict the Average Weight to the nearest pound for the 2022 Year. Group of answer choices A. 4057 pounds B. 4015 pounds C. This value of Year is beyond the scope of the…

How does utilizing linear regression benefit or help a business?

Please help me this question.