Answer:
The given regression equation is y=0.85x+4.11
Here,
x: thousands of automatic weapons
y=murders per 100,000 residents
A)
The expected murders per 100.000 residents in state with 11 thousands automatic weapons
we have to find value of y when x=11
y^= 0.85 * 11 + 4.11
y^=13.46
The expected murders per 100.000 residents in state with 11 thousands automatic weapons is 13.46
B)
The expected murders per 100.000 residents in state with 2.7 thousands automatic weapons
we have to find value of y when x=2.7
y^= 0.85 * 2.7 + 4.11
y^=6.405
The expected murders per 100.000 residents in state with 11 thousands automatic weapons is 6.405
B0/2.pl The table below shows the number of state-registered automatic weapons and the murder rate for...
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le table below shows the number of state-registered Itomatic weapons and the murder rate for several orthwestern states. 3 11.4 8.3 6.9 3.7 2.7 2.4 | 2.2 0.7 y 13.8 11.3 9.9 7.4 6.2 6.1 4.9 = thousands of automatic weapons = murders per 100,000 residents his data can be modeled by the equation = 0.85x + 4.14. Use this equation to answer the llowing; ecial Note: I suggest you verify this equation by :rforming linear regression on your calculator....
lists steps for TI-84 calculator. The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. * y 11.7 14.1 8 10.6 6.8 10.1 3.7 7.2 2.5 6. 3 2.4 6 2.2 6 0.8 4.6 = thousands of automatic weapons y-murders per 100,000 residents Determine the regression equation in y - ax + b form and write it below. (Round to 2 decimal places) A) How many murders per 100,000 residents can be...
PLEASE HELP!!!! THANK YOU!!! The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. 11.9 8.5 7 3.7 2.8 2.5 2.5 0.8 14.3 11.4 9.9 7.5 6.6 6.2 6.3 5 I thousands of automatic weapons y-murders per 100,000 residents This data can be modeled by the equation y = 0.843 + 4.23. Use this equation to answer the following: Special Note: I suggest you verify this equation by performing linear regression on...
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