| ##################################################################### |
| # Dataset Name: Lew (Beam Deflection Data) |
| # |
| # Description: This is an observed/"real world" data set |
| # consisting of 200 deflections of a steel-concrete |
| # beam while subjected to periodic pressure. |
| # The experimenter was H. S. Lew of the |
| # Center for Building Technology at NIST. |
| # We here use this data to test accuracy |
| # in summary statistics calculations. |
| # |
| # Stat Category: Univariate: Summary Statistics |
| # |
| # Reference: http://www.itl.nist.gov/div898/strd/univ/lew.html |
| # |
| # Data: "Real World" |
| # 1 Response : y = beam deflection |
| # 0 Predictors |
| # 200 Observations |
| # |
| # Model: Lower Level of Difficulty |
| # 2 Parameters : mu, sigma |
| # 1 Response Variable : y |
| # 0 Predictor Variables |
| # y = mu + e |
| ##################################################################### |
| |
| ##################################################################### |
| # |
| # Certified Values |
| # |
| ##################################################################### |
| n = 200 |
| mean = -177.435000000000 |
| standardDeviation = 277.332168044316 |
| autocorrelationCoefficient = -0.307304800605679 |
| |
| ##################################################################### |
| # |
| # R Generated Values |
| # |
| ##################################################################### |
| variance = 76913.13143 |
| max = 300 |
| min = -579 |
| sum = -35487 |
| |
| ##################################################################### |
| # |
| # Data |
| # |
| ##################################################################### |
| -213 |
| -564 |
| -35 |
| -15 |
| 141 |
| 115 |
| -420 |
| -360 |
| 203 |
| -338 |
| -431 |
| 194 |
| -220 |
| -513 |
| 154 |
| -125 |
| -559 |
| 92 |
| -21 |
| -579 |
| -52 |
| 99 |
| -543 |
| -175 |
| 162 |
| -457 |
| -346 |
| 204 |
| -300 |
| -474 |
| 164 |
| -107 |
| -572 |
| -8 |
| 83 |
| -541 |
| -224 |
| 180 |
| -420 |
| -374 |
| 201 |
| -236 |
| -531 |
| 83 |
| 27 |
| -564 |
| -112 |
| 131 |
| -507 |
| -254 |
| 199 |
| -311 |
| -495 |
| 143 |
| -46 |
| -579 |
| -90 |
| 136 |
| -472 |
| -338 |
| 202 |
| -287 |
| -477 |
| 169 |
| -124 |
| -568 |
| 17 |
| 48 |
| -568 |
| -135 |
| 162 |
| -430 |
| -422 |
| 172 |
| -74 |
| -577 |
| -13 |
| 92 |
| -534 |
| -243 |
| 194 |
| -355 |
| -465 |
| 156 |
| -81 |
| -578 |
| -64 |
| 139 |
| -449 |
| -384 |
| 193 |
| -198 |
| -538 |
| 110 |
| -44 |
| -577 |
| -6 |
| 66 |
| -552 |
| -164 |
| 161 |
| -460 |
| -344 |
| 205 |
| -281 |
| -504 |
| 134 |
| -28 |
| -576 |
| -118 |
| 156 |
| -437 |
| -381 |
| 200 |
| -220 |
| -540 |
| 83 |
| 11 |
| -568 |
| -160 |
| 172 |
| -414 |
| -408 |
| 188 |
| -125 |
| -572 |
| -32 |
| 139 |
| -492 |
| -321 |
| 205 |
| -262 |
| -504 |
| 142 |
| -83 |
| -574 |
| 0 |
| 48 |
| -571 |
| -106 |
| 137 |
| -501 |
| -266 |
| 190 |
| -391 |
| -406 |
| 194 |
| -186 |
| -553 |
| 83 |
| -13 |
| -577 |
| -49 |
| 103 |
| -515 |
| -280 |
| 201 |
| 300 |
| -506 |
| 131 |
| -45 |
| -578 |
| -80 |
| 138 |
| -462 |
| -361 |
| 201 |
| -211 |
| -554 |
| 32 |
| 74 |
| -533 |
| -235 |
| 187 |
| -372 |
| -442 |
| 182 |
| -147 |
| -566 |
| 25 |
| 68 |
| -535 |
| -244 |
| 194 |
| -351 |
| -463 |
| 174 |
| -125 |
| -570 |
| 15 |
| 72 |
| -550 |
| -190 |
| 172 |
| -424 |
| -385 |
| 198 |
| -218 |
| -536 |
| 96 |
