Answers_Assignment_1a

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Concordia University *

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677

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Statistics

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Apr 3, 2024

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EXERCISE 1 proc print data=sashelp.air; run; proc sgplot data=sashelp.air; series x=date y=air; run; Dataset has trend, seasonality and variance which can be removed through Log transformation and Lag4 differencing.
/* Log transformation and Lag4 differencing to stabilize the time series variation , remove trend and seasonality*/ data sashelp.air; set sashelp.air; log_lag4_air=log(air)-log(lag4(air)); run; /* Log transformation and Lag4 differencing plot */ proc sgplot data=sashelp.air; series x=date y=log_lag4_air; run;
From the new dataset: - Trend has been removed - Seasonality has been removed - Variance and level have been stabilized EXERCISE 2 Proc univariate data=tutorial.tourism; var trips; run;
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EXERCISE 4 Conduct the decomposition of the AIRPASS data. proc sgplot data=tutorial.airpass; series x=date y=passengers; run;
a) Does the data have a seasonal cycle? Yes, Data has a seasonal cycle. b) Is there a trend component in the data? If so, is it linear? Data has an upward trend component. c) Using Proc Expand find Moving averages: MA(3), MA(6), MA(12) for AIRPASS data (on Moodle). Explain each MA and differences between them.