An electronics company is looking to develop a regression model to predict the number of units sold for a special running watch. Data is provided below:
Sales (units) Price ($) Advertising ($) Holiday
500 100 50 Yes
480 120 40 Yes
485 110 45 No
510 103 55 Yes
490 108 40 No
488 109 30 No
496 106 45 Yes
1. Compile an excel spreadsheet for the above data and determine the regression equation.

3× __ -2=15 7 2× __+1=7 5 7× =22 15 5× __+10=2 8 × __+4=20 6 × =10 3 × __+2=8 6 × __+8=8 9 × __+7=20 6

What is the sum of these mixed numbers 4 2/3+ 3 1/9

Aprisoner is trapped in a cell containing three doors. the first door leads to a tunnel that returns him to his cell after two days of travel. the second leads to a tunnel that returns him to his cell after three days of travel. the third door leads immediately to freedom. (a) assuming that the prisoner will always select doors 1, 2 and 3 with probabili- ties 0.5,0.3,0.2 (respectively), what is the expected number of days until he reaches freedom? (b) assuming that the prisoner is always equally likely to choose among those doors that he has not used, what is the expected number of days until he reaches freedom? (in this version, if the prisoner initially tries door 1, for example, then when he returns to the cell, he will now select only from doors 2 and 3.) (c) for parts (a) and (b), find the variance of the number of days until the prisoner reaches freedom. hint for part (b): define ni to be the number of additional days the prisoner spends after initially choosing door i and returning to his cell.