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Add ins Hey Share Comments File Home Weert Draw Page Layout Formulas Review Data Areloks D From TexCry GE 2. Solwy Pa From Web [ Biting Connections Refresh Properties Filter Reapply What-if Forum Geography Data - From Table Bangs Advanced Analyst Shot R. T V W = C D E F G H L M P LSPL AUPL 2.6 151 21 41 4.19 0.051 7403 2.57 4 92 74 77. 3.42 D 251 D.OTTA 0.1135 #1.13 THAT 2.76 0.020 11.7 1.17 101.42 93.63 108 5 3.6 0.305 D. 126 0.52 7.16 25.44 41 56 4.18 87.15 THOS $7.1 0.0166 1.1 3.76 0.353 Q 487 11 2.45 1. 15 Doin Analysis 12 97.84 94.23 1,74 0.0419 7 50 11 12 TO 21 2.16 0 141 0.0291 3717 2.56 13 98.86 PLIT 103 5 0.371 0535 7.72 M 51 2.H1 16 15 81.84 0.0851 1.15 4.41 0.261 0.1195 0516 5.57 TH.41 3.74 19 0.172 20 97.08 105 4.30 0.245 0 500 21 20 37.95 010154 22 21 83.8 TA 76 2.35 10.02 11 23 D.0785 0.154 24 79.65 6LAT 2.54 0 154 D.046 0.0872 0.736 25 24 101.48 10 26 35 0.145 0 545 7.56 92 44 101 0571 12.0 2.20 T1 20 14. SheetiHow to run in EXCEL? P Search 14 Share Comment Data Raviow View Add-im Help File Home Draw Page Layout Formulas Clear allGroup Data Analysis Oh From Tew/CSV Does Recent Sources Queries & Cometions B Ungroup - 7 2, Solver To Reapply What-If Forecast from Web The Drifting Connections Properties Teat to Geography Subtotal Get Reharsh Stock Advanced Columns Ed - C Data > iffi From Table/Range The Edis Links fun M Ater Overies a Comedians Pris hom $ 1 U V M N P Q R S T C D E F G H ASPL loudhe's sharpens roug en fluctuation totally 3.32 $1.9 30196 1276 0 186 0.0576 0.0347 153 0.849 4.19 D 294 0.0541 0.430 95.32 91.4 Repression 78.05 73.3 D.132 6.0483 0.0345 1.685 TTT 0 251 0.0775 0.1135 92 74 inget Y Bangs $1.19 1 204 108 5 SDE O 0.0427 0.726 052 7.16 101.42 93.6 91.54 95,03 D 245 0.0 22 0.178 0.173 6.0493 6.0165 143 11 4.72 82.15 37.1 0 252 0.0786 0. 1935 1407 93.57 3.26 4.72 41 7.65 0.19 0.0819 0.169 01506 7.6 Output optiond 97 86 92.33 98.25 D.307 Input Y Range: 70.21 2.10 0.141 0.0479 0.0291 1.525 M.17 103 5 3.78 0.371 annoyance data 80.13 74.51 31.95 2 21 0 17T 0.0561 0.0314 25 3 0.927 ON Workbook 0.189 0.0752 0.0251 1.15 4.6 3.31 0 261 0.0758 0.1195 0.516 557 92.06 0.0200 4.4 2 24 0.0734 1 09 Input X Range: 0.172 0.5.14 0 265 G.0828 0.178 3.506 Formal Probably 97 08 105 Somail Probably Plofu LSPL, ASPL, loudness, 0 18 0.0158 4.84 01021 11 1 14 3.8 78.76 0.181 6.0538 sharpness, roughness, 92.94 TH, 15 0 334 0.075 0.154 0,459 0.0572 0.746 79.66 60.47 0154 0.237 0.534 fluctuation, totality, 101.48 92 5 105 3.71 0 269 0.0892 0.0793 0.145 3.545 95.2 92.53 3.521 Al, impulsiveness 92.44 105 0 247 0.081 0.198 0.0332 25 2 0.846 1. BE 80.53 32.6 2.26 D 235 0.0658 0.18 0.0865 0.02:35 14 1.05 data Sheet!How to run in EXCEL? SUMMARY OUTPUT Regression Statistics Multiple R 0.96724246 R Square 0.93555798 Adjusted R Square 0.92105852 Standard Error 0.50121848 Observations 50 ANOVA of 55 MS F Significance F Regression 9 145.8866895 16.2096 64.5237 5.44122E-21 Residual 40 10.0487985 0.25122 Total 49 155.935488 Coefficients Standard Error |t Stat P-value Lower 95* Upper 95# Lower 95.0* Upper 95.0* Note that all the Intercept -6.93439506 12.60496155 -0.5501 0.58529 -32.4099726 18.5411825 -32.4099726 18.5411825 significance value less LSPL 0.04270954 0.061694041 0.69228 0.49276 -0.08197877 0.16739784 -0.08197877 0.16739784 ASPL 0.02914658 0.13240057 0.22014 0.82688 -0.23844495 0.29673812 -0.23844495 0.29673812 than 0.05 will be the loudness -0.00407558 0.037902206 -0.1075 0.91491 -0.08067879 0.07252764 -0.08067879 0.07252764 significant predictor/s sharpness 1.23397507 0.533046629 2.31495 0.02583 0.156647651 2.3113025 0.15664765 2.3113025 for the annoyance roughness 6.94529499 3.166663237 2.19325 0.03416 0.545229848 13.3453601 0.54522985 13.3453601 fluctuation 1.5546629 13.97315212 0.11126 0.91197 -26.686131 29.7954568 -26.686131 29.7954568 totality 2.45630096 2.933887477 0.83722 0.40744 -3.47330682 8.38590874 -3.47330682 8.38590874 Al -0.00238971 0.036489323 -0.0655 0.94811 -0.07613738 0.07135796 -0.07613738 0.07135796 impulsiveness 1.15720901 0.655023447 1.76667 0.08491 -0.16664276 2.48106077 -0.16664276 2.48106077Interpretation: Rsquare: > 93.6% of the variation of the annoyance was explained by the model (specifically the roughness and the sharpness of the sound). Only 5.4% was not explained by the model. ANOVA significance value: The model is significant in explaining the annoyance Model: Annoyance = 6.945(roughness) + 1.234(sharpness) For every unit increase in the roughness of the sound, the annoyance increases by 6.945 units on the average, holding the other variable constant. For every unit increase in the sharpness of the sound, the annoyance increases by 1.234 units on the average, holding the other variable constant