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1.
Exploratory Data Analysis
1.4. EDA Case Studies 1.4.2. Case Studies 1.4.2.3. Random Walk
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| Generation |
A random walk can be generated from a set of uniform
random numbers by the formula:
The motivation for studying a set of random walk data is to illustrate the effects of a known underlying autocorrelation structure (i.e., non-randomness) in the data. |
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| Software | The analyses used in this case study can be generated using both Dataplot code and R code. The reader can download the data as a text file. | ||
| Data |
The following is the set of random walk numbers used for
this case study.
-0.399027 -0.645651 -0.625516 -0.262049 -0.407173 -0.097583 0.314156 0.106905 -0.017675 -0.037111 0.357631 0.820111 0.844148 0.550509 0.090709 0.413625 -0.002149 0.393170 0.538263 0.070583 0.473143 0.132676 0.109111 -0.310553 0.179637 -0.067454 -0.190747 -0.536916 -0.905751 -0.518984 -0.579280 -0.643004 -1.014925 -0.517845 -0.860484 -0.884081 -1.147428 -0.657917 -0.470205 -0.798437 -0.637780 -0.666046 -1.093278 -1.089609 -0.853439 -0.695306 -0.206795 -0.507504 -0.696903 -1.116358 -1.044534 -1.481004 -1.638390 -1.270400 -1.026477 -1.123380 -0.770683 -0.510481 -0.958825 -0.531959 -0.457141 -0.226603 -0.201885 -0.078000 0.057733 -0.228762 -0.403292 -0.414237 -0.556689 -0.772007 -0.401024 -0.409768 -0.171804 -0.096501 -0.066854 0.216726 0.551008 0.660360 0.194795 -0.031321 0.453880 0.730594 1.136280 0.708490 1.149048 1.258757 1.102107 1.102846 0.720896 0.764035 1.072312 0.897384 0.965632 0.759684 0.679836 0.955514 1.290043 1.753449 1.542429 1.873803 2.043881 1.728635 1.289703 1.501481 1.888335 1.408421 1.416005 0.929681 1.097632 1.501279 1.650608 1.759718 2.255664 2.490551 2.508200 2.707382 2.816310 3.254166 2.890989 2.869330 3.024141 3.291558 3.260067 3.265871 3.542845 3.773240 3.991880 3.710045 4.011288 4.074805 4.301885 3.956416 4.278790 3.989947 4.315261 4.200798 4.444307 4.926084 4.828856 4.473179 4.573389 4.528605 4.452401 4.238427 4.437589 4.617955 4.370246 4.353939 4.541142 4.807353 4.706447 4.607011 4.205943 3.756457 3.482142 3.126784 3.383572 3.846550 4.228803 4.110948 4.525939 4.478307 4.457582 4.822199 4.605752 5.053262 5.545598 5.134798 5.438168 5.397993 5.838361 5.925389 6.159525 6.190928 6.024970 5.575793 5.516840 5.211826 4.869306 4.912601 5.339177 5.415182 5.003303 4.725367 4.350873 4.225085 3.825104 3.726391 3.301088 3.767535 4.211463 4.418722 4.554786 4.987701 4.993045 5.337067 5.789629 5.726147 5.934353 5.641670 5.753639 5.298265 5.255743 5.500935 5.434664 5.588610 6.047952 6.130557 5.785299 5.811995 5.582793 5.618730 5.902576 6.226537 5.738371 5.449965 5.895537 6.252904 6.650447 7.025909 6.770340 7.182244 6.941536 7.368996 7.293807 7.415205 7.259291 6.970976 7.319743 6.850454 6.556378 6.757845 6.493083 6.824855 6.533753 6.410646 6.502063 6.264585 6.730889 6.753715 6.298649 6.048126 5.794463 5.539049 5.290072 5.409699 5.843266 5.680389 5.185889 5.451353 5.003233 5.102844 5.566741 5.613668 5.352791 5.140087 4.999718 5.030444 5.428537 5.471872 5.107334 5.387078 4.889569 4.492962 4.591042 4.930187 4.857455 4.785815 5.235515 4.865727 4.855005 4.920206 4.880794 4.904395 4.795317 5.163044 4.807122 5.246230 5.111000 5.228429 5.050220 4.610006 4.489258 4.399814 4.606821 4.974252 5.190037 5.084155 5.276501 4.917121 4.534573 4.076168 4.236168 3.923607 3.666004 3.284967 2.980621 2.623622 2.882375 3.176416 3.598001 3.764744 3.945428 4.408280 4.359831 4.353650 4.329722 4.294088 4.588631 4.679111 4.182430 4.509125 4.957768 4.657204 4.325313 4.338800 4.720353 4.235756 4.281361 3.795872 4.276734 4.259379 3.999663 3.544163 3.953058 3.844006 3.684740 3.626058 3.457909 3.581150 4.022659 4.021602 4.070183 4.457137 4.156574 4.205304 4.514814 4.055510 3.938217 4.180232 3.803619 3.553781 3.583675 3.708286 4.005810 4.419880 4.881163 5.348149 4.950740 5.199262 4.753162 4.640757 4.327090 4.080888 3.725953 3.939054 3.463728 3.018284 2.661061 3.099980 3.340274 3.230551 3.287873 3.497652 3.014771 3.040046 3.342226 3.656743 3.698527 3.759707 4.253078 4.183611 4.196580 4.257851 4.683387 4.224290 3.840934 4.329286 3.909134 3.685072 3.356611 2.956344 2.800432 2.761665 2.744913 3.037743 2.787390 2.387619 2.424489 2.247564 2.502179 2.022278 2.213027 2.126914 2.264833 2.528391 2.432792 2.037974 1.699475 2.048244 1.640126 1.149858 1.475253 1.245675 0.831979 1.165877 1.403341 1.181921 1.582379 1.632130 2.113636 2.163129 2.545126 2.963833 3.078901 3.055547 3.287442 2.808189 2.985451 3.181679 2.746144 2.517390 2.719231 2.581058 2.838745 2.987765 3.459642 3.458684 3.870956 4.324706 4.411899 4.735330 4.775494 4.681160 4.462470 3.992538 3.719936 3.427081 3.256588 3.462766 3.046353 3.537430 3.579857 3.931223 3.590096 3.136285 3.391616 3.114700 2.897760 2.724241 2.557346 2.971397 2.479290 2.305336 1.852930 1.471948 1.510356 1.633737 1.727873 1.512994 1.603284 1.387950 1.767527 2.029734 2.447309 2.321470 2.435092 2.630118 2.520330 2.578147 2.729630 2.713100 3.107260 2.876659 2.774242 3.185503 3.403148 3.392646 3.123339 3.164713 3.439843 3.321929 3.686229 3.203069 3.185843 3.204924 3.102996 3.496552 3.191575 3.409044 3.888246 4.273767 3.803540 4.046417 4.071581 3.916256 3.634441 4.065834 3.844651 3.915219 |
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