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Multiple linear regression results:


Dependent Variable: Residuals
Independent Variable(s): 2016, 2019
Residuals = -47874.133 + -0.11229636 2016 + 1 2019

Parameter estimates:


ParameterEstimateStd. Err.AlternativeDFT-StatP-value
Intercept-47874.1331.1897923e-9 ≠ 02-4.0237388e13<0.0001
2016-0.112296367.0431931e-15 ≠ 02-1.5943957e13<0.0001
201912.4309636e-14 ≠ 024.1135952e13<0.0001

Analysis of variance table for multiple regression model:


SourceDFSSMSF-statP-value
Model223022715115113588.4608327e26<0.0001
Error22.7210933e-201.3605467e-20
Total423022715

Summary of fit:


Root MSE: 1.1664247e-10
R-squared: 1
R-squared (adjusted): 1
Residuals stored in new column: Residuals
Multiple Linear Regression
bcd9eac4-38da-4210-98be-740e75a6d779-47818_d2l_snhumlpApr 19, 20194KB4

Multiple linear regression results:


Dependent Variable: var4
Independent Variable(s): var1, var2, var3

All subsets:


VariablesNumberRMSER-squaredR-squared (adj)Rank
var1, var2, var332.47998090.80140.76411
var1, var322.49628150.78620.7612
var1, var222.5431660.77810.75194
var2, var322.55653470.77570.74935
var212.51024220.7710.75833
var112.81976850.71110.6956
var315.19261170.0203-0.03417


Results for model with maximum adjusted R-squared:


var4 = 117.08469 + 4.334092 var1 + -2.8568479 var2 + -2.1860603 var3

Parameter estimates:


ParameterEstimateStd. Err.AlternativeDFT-StatP-value
Intercept117.0846999.782403 ≠ 0161.17340020.2578
var14.3340923.0155114 ≠ 0161.4372660.1699
var2-2.85684792.5820153 ≠ 016-1.10644110.2849
var3-2.18606031.595499 ≠ 016-1.3701420.1896

Analysis of variance table for multiple regression model:


SourceDFSSMSF-statP-value
Model3396.98461132.328221.515712<0.0001
Error1698.4048886.1503055
Total19495.3895

Summary of fit:


Root MSE: 2.4799809
R-squared: 0.8014
R-squared (adjusted): 0.7641
Multiple Linear Regression
53673285_ecollege_uarkssoApr 19, 20196KB4

Multiple linear regression results:


Dependent Variable: var4
Independent Variable(s): var1, var2, var3

All subsets:


VariablesNumberRMSER-squaredR-squared (adj)Rank
var1, var2, var332.47998090.80140.76411
var1, var322.49628150.78620.7612
var1, var222.5431660.77810.75194
var2, var322.55653470.77570.74935
var212.51024220.7710.75833
var112.81976850.71110.6956
var315.19261170.0203-0.03417


Results for model with maximum adjusted R-squared:


var4 = 117.08469 + 4.334092 var1 + -2.8568479 var2 + -2.1860603 var3

Parameter estimates:


ParameterEstimateStd. Err.AlternativeDFT-StatP-value
Intercept117.0846999.782403 ≠ 0161.17340020.2578
var14.3340923.0155114 ≠ 0161.4372660.1699
var2-2.85684792.5820153 ≠ 016-1.10644110.2849
var3-2.18606031.595499 ≠ 016-1.3701420.1896

Analysis of variance table for multiple regression model:


SourceDFSSMSF-statP-value
Model3396.98461132.328221.515712<0.0001
Error1698.4048886.1503055
Total19495.3895

Summary of fit:


Root MSE: 2.4799809
R-squared: 0.8014
R-squared (adjusted): 0.7641
Multiple Linear Regression
53673285_ecollege_uarkssoApr 19, 20196KB2

Multiple linear regression results:


Dependent Variable: var1
Independent Variable(s): var2, var3, var4, var5
var1 = -18.981345 + -1.184609 var2 + 1.2042393 var3 + -0.08662215 var4 + 0.011361886 var5

Parameter estimates:


ParameterEstimateStd. Err.AlternativeDFT-StatP-value
Intercept-18.981345248.0125 ≠ 015-0.0765338250.94
var2-1.1846097.6422744 ≠ 015-0.155007390.8789
var31.20423936.3894333 ≠ 0150.188473570.853
var4-0.086622154.0223627 ≠ 015-0.0215351420.9831
var50.0113618860.5962575 ≠ 0150.0190553350.985

Analysis of variance table for multiple regression model:


SourceDFSSMSF-statP-value
Model4140.2219735.0554931.00200920.437
Error15524.7780334.985202
Total19665

Summary of fit:


Root MSE: 5.914829
R-squared: 0.2109
R-squared (adjusted): 0.0004
Multiple Linear Regression project
36686717_ecollege_uarkssoApr 17, 20194KB3

Multiple linear regression results:


Dependent Variable: PTS
Independent Variable(s): 3P%, FG%, FT%
PTS = -35.314109 + 2.2866363 3P% + 61.307925 FG% + 33.385445 FT%

Parameter estimates:


ParameterEstimateStd. Err.AlternativeDFT-StatP-value
Intercept-35.31410910.83819 ≠ 036-3.25830330.0024
3P%2.28663634.791553 ≠ 0360.477222370.6361
FG%61.30792512.617139 ≠ 0364.8590989<0.0001
FT%33.3854458.3310071 ≠ 0364.0073720.0003

Analysis of variance table for multiple regression model:


SourceDFSSMSF-statP-value
Model3198.5263766.1754579.050920.0001
Error36263.212637.3114619
Total39461.739

Summary of fit:


Root MSE: 2.7039715
R-squared: 0.43
R-squared (adjusted): 0.3824
Multiple Linear Regression
bms0062Apr 16, 20194KB4

Multiple linear regression results:


Dependent Variable: Time spent on social media/ day
Independent Variable(s): Age, Weight
Time spent on social media/ day = 318.7384 + -15.734061 Age + 3.2930058 Weight

Parameter estimates:


ParameterEstimateStd. Err.AlternativeDFT-StatP-value
Intercept318.7384293.76396 ≠ 0221.08501530.2897
Age-15.73406114.371044 ≠ 022-1.09484470.2854
Weight3.29300581.1602285 ≠ 0222.8382390.0096

Analysis of variance table for multiple regression model:


SourceDFSSMSF-statP-value
Model245891.56822945.7844.03851640.0321
Error22124998.195681.736
Total24170889.76

Summary of fit:


Root MSE: 75.377291
R-squared: 0.2685
R-squared (adjusted): 0.202
Multiple Linear Regression=
34772087_ecollege_msumlpApr 16, 20193KB3

Multiple linear regression results:


Dependent Variable: Paynet Master Score V2
Independent Variable(s): Time In Business, Number of Employees, Funding Amount
Paynet Master Score V2 = 673.76394 + 0.87701424 Time In Business + -0.0000012934068 Number of Employees + 0.0000069010674 Funding Amount

Parameter estimates:


ParameterEstimateStd. Err.AlternativeDFT-StatP-value
Intercept673.763943.5640891 ≠ 0157189.0424<0.0001
Time In Business0.877014240.16480913 ≠ 01575.3213935<0.0001
Number of Employees-0.00000129340680.00001946204 ≠ 0157-0.0664579250.9471
Funding Amount0.00000690106740.000022061421 ≠ 01570.312811550.7548

Analysis of variance table for multiple regression model:


SourceDFSSMSF-statP-value
Model315502.5125167.50399.7857369<0.0001
Error15782906.184528.06487
Total16098408.696

Summary of fit:


Root MSE: 22.979662
R-squared: 0.1575
R-squared (adjusted): 0.1414
Multiple Linear Regression
jbonafedApr 6, 20194KB11

Multiple linear regression results:


Dependent Variable: Year
Independent Variable(s): Month
Year = 1937.8386 + -0.090667019 Month

Parameter estimates:


ParameterEstimateStd. Err.AlternativeDFT-StatP-value
Intercept1937.83860.4069145 ≠ 0604762.2747<0.0001
Month-0.0906670190.055987795 ≠ 060-1.61940690.1106

Analysis of variance table for multiple regression model:


SourceDFSSMSF-statP-value
Model16.02496966.02496962.62247860.1106
Error60137.8462.2974333
Total61143.87097

Summary of fit:


Root MSE: 1.5157286
R-squared: 0.0419
R-squared (adjusted): 0.0259
Multiple Linear Regression
f9416dbe-89f6-457c-99a5-91c5f32fe871-164470_d2l_snhumlpFeb 15, 20193KB25

Multiple linear regression results:


Dependent Variable: MMXT
Independent Variable(s): MMNT
MMXT = 98.561833 + 1.0614989 MMNT

Parameter estimates:


ParameterEstimateStd. Err.AlternativeDFT-StatP-value
Intercept98.5618332.1682321 ≠ 06045.457234<0.0001
MMNT1.06149890.022856422 ≠ 06046.442044<0.0001

Analysis of variance table for multiple regression model:


SourceDFSSMSF-statP-value
Model1554591.25554591.252156.8634<0.0001
Error6015427.716257.12859
Total61570018.97

Summary of fit:


Root MSE: 16.03523
R-squared: 0.9729
R-squared (adjusted): 0.9725
Multiple Linear Regression
f9416dbe-89f6-457c-99a5-91c5f32fe871-164470_d2l_snhumlpFeb 15, 20193KB14

Multiple linear regression results:


Dependent Variable: Sales
Independent Variable(s): t, Q1, Q2, Q3
Sales = 1377.5927 + 70.594849 t + -189.0093 Q1 + 501.48431 Q2 + 310.40177 Q3

Parameter estimates:


ParameterEstimateStd. Err.AlternativeDFT-StatP-value
Intercept1377.5927115.92225 ≠ 04711.883764<0.0001
t70.5948492.8282134 ≠ 04724.960934<0.0001
Q1-189.0093120.02426 ≠ 047-1.57475910.122
Q2501.48431119.85754 ≠ 0474.18400320.0001
Q3310.40177119.75739 ≠ 0472.59192170.0127

Analysis of variance table for multiple regression model:


SourceDFSSMSF-statP-value
Model46244367115610918167.5532<0.0001
Error474378986.293169.919
Total5166822657

Summary of fit:


Root MSE: 305.23748
R-squared: 0.9345
R-squared (adjusted): 0.9289
Multiple Linear Regression
lippert.49Dec 4, 20184KB22
Multiple Linear Regressionwest.866Dec 4, 2018174B25
Multiple Linear Regressionwest.866Nov 30, 2018174B32

Multiple linear regression results:


Dependent Variable: ID
Independent Variable(s): BED, TDAYS, % PRIVATE PAY
ID = 17.116585 + -0.10583703 BED + 0.027597802 TDAYS + 0.10400362 % PRIVATE PAY

Parameter estimates:


ParameterEstimateStd. Err.AlternativeDFT-StatP-value
Intercept17.1165854.4436355 ≠ 0263.85193280.0007
BED-0.105837030.053576534 ≠ 026-1.97543640.0589
TDAYS0.0275978020.018554821 ≠ 0261.48736560.1489
% PRIVATE PAY0.104003620.15573412 ≠ 0260.667828120.5101

Analysis of variance table for multiple regression model:


SourceDFSSMSF-statP-value
Model3372.72969124.243231.72305050.1868
Error261874.770372.10655
Total292247.5

Summary of fit:


Root MSE: 8.4915576
R-squared: 0.1658
R-squared (adjusted): 0.0696
Residuals stored in new column: Residuals
Multiple Linear Regression
kyle.hozeyNov 29, 20184KB52
Multiple Linear RegressionajthalNov 28, 2018174B22
Multiple Linear Regression Graphat866915Nov 27, 2018174B36

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