Data on England and Wales conceptions wider 18.
Part 1
Produce a report on these figures including:
(1) A graph showing how these figures moved throughout the time period.
(2) From your graph in (1) give reasons as to whether you think a multiplicative or additive model is likely to be better here.
(3) A centred trend based on a method of moving averages on the figures in the published data.
(4) A set of adjusted seasonal variations based on your own analysis for the figures.
(5) A column showing the residuals from your model.
(6) A set of your own deseasonalised figures based on your analysis.
(7) A suitable graphical presentation of these series.
NB You should use excel for this question.
Part 2
Enter the figures into minitab and
(1) Use the Decomposition facility under stat menu to obtain seasonal variations, trend and deseasonalised figures using an additive model.
(2) Produce and comment the graphical representation showing trend and fitted model.
(3) Compare your pattern of residuals with that from the minitab model (hint: you might look at means and standard deviations and charts).
(4) Perform an analysis using autocorrelation and partial autocorrelation of the residuals in minitab. What do the autocorrelation and partial autocorrelation tell you about the residuals here?
Teenage conceptions England and Wales:
December
|
2003
|
10.749
|
March
|
2004
|
10.854
|
June
|
2004
|
10,570
|
September
|
2004
|
9.967
|
December
|
2004
|
10.807
|
March
|
2005
|
10,400
|
June
|
2005
|
10,464
|
September
|
2005
|
10.437
|
December
|
2005
|
11.024
|
March
|
2006
|
10,192
|
June
|
2006
|
10,550
|
September
|
2006
|
9.987
|
December
|
2006
|
11.039
|
March
|
2007
|
10.846
|
June
|
2007
|
10.932
|
September
|
2007
|
10.353
|
December
|
2007
|
10.857
|
March
|
2008
|
10.730
|
June
|
2008
|
10.576
|
September
|
2008
|
9,894
|
December
|
2008
|
10.161
|
March
|
2009
|
9.779
|
June
|
2009
|
10.046
|
September
|
2009
|
9,154
|
December
|
2009
|
9.280
|
March
|
2010
|
9.218
|
June
|
2010
|
9,098
|
September
|
2010
|
8,091
|
December
|
2010
|
8.226
|
March
|
2011
|
7.844
|
June
|
2011
|
8.347
|
September
|
2011
|
7,458
|
December
|
2011
|
7.402
|
March
|
2012
|
7.597
|
June
|
2012
|
7,083
|
September
|
2012
|
6,540
|
December
|
2012
|
6,614
|
March
|
2013
|
6.282
|
June
|
2013
|
6,279
|
September
|
2013
|
5.598
|
December
|
2013
|
6,147
|
March
|
2014
|
5,878
|
June
|
2014
|
5.740
|
Attachment:- Report Assignment in Time series.docx