Each year a nationally recognized publication conducts its 'survey of america's best graduate and professional schools.' an academic advisor wants to predict the typical starting salary of a graduate at a top business school using gmat score of the school as a predictor variable. total gmat scores range from 200 to 800. a simple linear regression of salary versus gmat using 25 data points yields the regression equation given below. y = 228x - 92,040 give an interpretation of the y-intercept. the value has no practical interpretation since a gmat of 0 is nonsensical and outside the range of the sample data. we estimate the base salary of graduates of a top business school to be $-92,040. we estimate salary to decrease $92,040 for every 1-point increase in gmat. we expect to predict salary to within 2(92040) = $184,080 of its true value using gmat in a straight-line model.

1foot = 12 inches; 1 yard = 3 feet

Evaluate 3(a + b + c)squared for a = 2, b = 3, and c = 4. a. 54 b. 243 c.729 add solution .

Acaterer knows he will need 60, 50, 80, 40 and 50 dinner napkins on five successive evenings. he can purchase new napkins initially at 25 cents each, after which he can have dirty napkins laundered by a fast one-day laundry service (i. e., dirty napkins given at the end of the day will be ready for use the following day) at 15 cents each, or by a slow two-day service at 8 cents each or both. the caterer wants to know how many napkins he should purchase initially and how many dirty napkins should be laundered by fast and slow service on each of the days in order to minimize his total costs. formulate the caterer’s problem as a linear program as follows (you must state any assumptions you make): a. define all variables clearly. how many are there? b. write out the constraints that must be satisfied, briefly explaining each. (do not simplify.) write out the objective function to be minimized. (do not simplify.)