9.9. Time Series Analysis 561
Table 9.8.1: Parameters to compute the correlation coefficient for the example
above. The last row is the sum of each column.
x y xy x^2 y^2102 28 10404 784 2856154 98 23716 9604 15092200 132 40000 17424 26400220 98 48400 9604 21560267 129 71289 16641 34443263 202 69169 40804 53126352 265 123904 70225 93280361 243 130321 59049 87723423 291 178929 84681 123093449 324 201601 104976 145476512 376 262144 141376 192512598 412 357604 169744 246376601 524 361201 274576 314924701 511 491401 261121 358211711 560 505521 313600 3981605914 4193 2875604 1574209 2113232
9.9 TimeSeriesAnalysis...........................
Most experiments involve taking data at regular intervals of time. These time series
data are then analyzed using different techniques. The analysis depends on the
application and the inferences to be drawn from the data. For example, one might
be interested in simply determining the expectation value of the variables involved
or a much complicated task of identifying the hidden structures in the time series.
In the following sections we will discuss some of the important techniques used in
time series analysis.