In: Statistics and Probability
Consider the following times-series where the data is recorded weekly
Data collected over 36 weeks
| 
 t  | 
 X  | 
 t  | 
 X  | 
 t  | 
 X  | 
 t  | 
 X  | 
 t  | 
 X  | 
 t  | 
 X  | 
| 
 1  | 
 9.8  | 
 7  | 
 36.4  | 
 13  | 
 53.4  | 
 19  | 
 99.2  | 
 25  | 
 105.3  | 
 31  | 
 141.3  | 
| 
 2  | 
 9.0  | 
 8  | 
 51.0  | 
 14  | 
 66.6  | 
 20  | 
 90.4  | 
 26  | 
 116.7  | 
 32  | 
 151.8  | 
| 
 3  | 
 10.5  | 
 9  | 
 51.1  | 
 15  | 
 70.6  | 
 21  | 
 91.2  | 
 27  | 
 113.2  | 
 33  | 
 151.1  | 
| 
 4  | 
 20.6  | 
 10  | 
 46.9  | 
 16  | 
 76.4  | 
 22  | 
 94.9  | 
 28  | 
 120.5  | 
 34  | 
 156.4  | 
| 
 5  | 
 28.1  | 
 11  | 
 50.5  | 
 17  | 
 88.4  | 
 23  | 
 94.2  | 
 29  | 
 124.2  | 
 35  | 
 155.9  | 
| 
 6  | 
 28.3  | 
 12  | 
 58.5  | 
 18  | 
 98.6  | 
 24  | 
 104.1  | 
 30  | 
 130.2  | 
 36  | 
 160.0  | 
Assess the level of serial correlation. Is there a reason for concern? Justify your answer.
x=c(9.8,9.0,10.5,20.6,28.1,28.3,36.4,51.0,51.1,46.9,50.5,58.5,53.4,66.6,70.6,76.4,88.4,98.6,99.2,90.4,91.2,94.9,94.2,104.1,105.3,116.7,113.2,120.5,124.2,130.2,141.3,151.8,151.1,156.4,155.9,160.0)
serialCorrelationTest(x, test = "rank.von.Neumann",
alternative = "two.sided", conf.level = 0.95)

Here from the serial correlation test the p value is 0.04<0.05. Hence we reject the null hypothesis that is rho =0.