Connfused.

[yr12]

Year                                                 1        2        3         4          5         6           7          8           9         10
Average number of days absent           6.8       6.9     7.6       8.1       7.4      8.6         8.6       9.1        9           9.9

After a big effort, the absence rate in 2003 (x = 11) actually dropped to 6.5. Estimate the average number of extra days that students are at school in 2003 compared to the prediction (answer to one decimal place)

Absolutely no idea for this one.  

[Visionz]

Year                                                 1        2        3         4          5         6           7          8           9         10       11
Average number of days absent           6.8       6.9     7.6       8.1       7.4      8.6         8.6       9.1        9           9.9         6.5

3.4 more days a year?

[yr12]

hm could it be that simple? I dont have the answer for this so im not sure but seems too easy :s. although its only worth 1 mark.

[Blakhitman]

Don't you have to use the regression line to predict the 11th value, then find the difference between the predicted and the actual (6.5)?

[yr12]

Yep ^^ thats right. I asked my friend and he said the same thing.

Quarter          1          2         3         4
1998          7.16        7.23     7.36     7.36
1999          6.96       6.76      6.76     6.71
2000          6.15       6.29       6.16    6.18

Estimate the yearly drop rate in deseasonalised unemployment from 1998 to 2000. Give answer as a percentage to 2 decimal places.

[kenhung123]

First deseasonalise the data (using the formula) then find the gradient of data.

[yr12]

That is deseasonalised data however this question has already been asked before. we were told to find the regression line of the deseasonalised data. I doubt they would ask the same question twice but jsut in a different method.