I have this set of numbers

Year Gass

1982 | 5464

1984 | 5710

1986 | 5718

1988 | 6113

1990 | 6115

1992 | 6200

1994 | 6392

1996 | 6607

1998 | 6690

2000 | 6933

2002 | 6891

I plugged this in to a table on my TI-84 to find the regression and do the scatter plot

There are 6 questions associated with this data. I THINK I solved the first 5 right, here is what i have.

1) Do scatter plot and find linear regression with only the first 10

-Did the graph fine and went to stat/calc/ LinReg (ax+b) and used this 73.67272727x - 140498.5273

2) what does your linear model predict will be the emissions for 2002, how does this compare with actual emissions.

- I pluged 2002 in for x so I had: 73.67272727(2002) - 140498.5273

The linear model predicted 7042 compared to the actual of 6891 which was a difference 151.

3)Apply ALL data to find the best linear model.- For this I am not sure if I did this right. I went to stat/calc/ and tried the LinReg, QuadRed, and CubReg to find which would give me the closest value to the actual when plugging a yearin for x. I found that the CubReg was the closest.

4) which model do you have the most confidence to predict emissions levels.- Again I dont think I did this right, I found the LinReg, QuadReg, and CubicReg equations and plugged a year into each of the x for each equation and found that cubic came the closest to the actual so I said that was

5) Interpret practical meaning of the slope of the regression line

- I have no idea

6) In what year did the best model predict the emissions will reach 10 billion tons-Need help on this one too

PLEASE, someone help me with this I will be very greatful