Following is a dataset:

Qty     Price    Advertising    Income
42100   11.77    46100          38000
55500   9.96     47200          39100
71100   12.36    60900          40100
63200   12.49    55600          44200
77200   10.68    64400          41800
70900   12.07    60700          44800
55600   11.97    52100          39900
70700   11.23    57900          43600
71400   11.26    55600          41700
79400   9.79     60100          41200
60600   12.29    50700          44000
50800   12.70    46500          43300
61800   12.33    58600          41000
40500   10.88    42800          38300
85300   10.14    64800          42100

Say you have 3 simple regression equations:
Qty = 117763-4713*Price
t-statPrice = -1.35, SEE = 12800, R2=12.3%, Adj R2 = 5.5%, F-stat = 1.82

Qty = -32655+1.75*Advertising
t-statPrice = 9.43, SEE = 4883, R2=87.2%, Adj R2 = 86.3%, F-stat = 88.84

Qty = -58386+2.94*Income
t-statPrice = 1.99, SEE = 11962, R2=23.4%, Adj R2 = 17.5%, F-stat = 3.97

A) Which of the independent variables are significant and at what confidence level?

B) What is the difference between each simple regression coefficient
estimate and that which might be estimated using a multiple regression
approach involving all three independent variables?