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Simple linear regression results:


Dependent Variable: SALARY
Independent Variable: Record_ID#
SALARY = 3235706 + 91581.951 Record_ID#
Sample size: 30
R (correlation coefficient) = 0.26865602
R-sq = 0.072176059
Estimate of error standard deviation: 4154905.4

Parameter estimates:


ParameterEstimateStd. Err.AlternativeDFT-StatP-value
Intercept32357061693506.7 ≠ 0281.91065440.0663
Slope91581.95162053.614 ≠ 0281.4758520.1511

Analysis of variance table for regression model:


SourceDFSSMSF-statP-value
Model13.7601736e133.7601736e132.17813910.1511
Error284.8337068e141.7263239e13
Total295.2097242e14
Simple Linear Regression
kalinrossJun 18, 20193KB1
Simple Linear RegressionkalinrossJun 18, 2019174B1
Simple Linear Regressionc656875a-089c-4fe5-a048-8612233416a8-147943_d2l_snhumlpJun 13, 2019174B7
Simple Linear Regression
Scatter plot with fitted line
kelliernJun 13, 2019174B6

Simple linear regression results:


Dependent Variable: Hrs slept when not working
Independent Variable: Hrs slept prior to working
Hrs slept when not working = 8.9338536 - 0.18656284 Hrs slept prior to working
Sample size: 86
R (correlation coefficient) = -0.27958475
R-sq = 0.078167631
Estimate of error standard deviation: 1.2912444

Parameter estimates:


ParameterEstimateStd. Err.AlternativeDFT-StatP-value
Intercept8.93385360.40508613 ≠ 08422.054208<0.0001
Slope-0.186562840.069903352 ≠ 084-2.66886830.0091

Analysis of variance table for regression model:


SourceDFSSMSF-statP-value
Model111.87602611.8760267.1228580.0091
Error84140.054211.667312
Total85151.93023
Simple Linear Regression
Correlation coefficient
kelliernJun 13, 20193KB7

Simple linear regression results:


Dependent Variable: mmnt
Independent Variable: mmxt
mmnt = -90.859575 + 0.92252252 mmxt
Sample size: 62
R (correlation coefficient) = 0.98842669
R-sq = 0.97698733
Estimate of error standard deviation: 14.216979

Parameter estimates:


ParameterEstimateStd. Err.AlternativeDFT-StatP-value
Intercept-90.8595752.9548656 ≠ 060-30.74914<0.0001
Slope0.922522520.018278494 ≠ 06050.470378<0.0001

Analysis of variance table for regression model:


SourceDFSSMSF-statP-value
Model1514858.33514858.332547.2591<0.0001
Error6012127.349202.12248
Total61526985.68
Simple Linear Regression
2b76696e-fa37-4186-8205-290464905c9a-171056_d2l_snhumlpJun 13, 20193KB7

Simple linear regression results:


Dependent Variable: MMNT
Independent Variable: MMXT
MMNT = -102.0713 + 0.98220162 MMXT
Sample size: 61
R (correlation coefficient) = 0.98682358
R-sq = 0.97382079
Estimate of error standard deviation: 15.098896

Parameter estimates:


ParameterEstimateStd. Err.AlternativeDFT-StatP-value
Intercept-102.07133.3812064 ≠ 059-30.187835<0.0001
Slope0.982201620.020965895 ≠ 05946.847588<0.0001

Analysis of variance table for regression model:


SourceDFSSMSF-statP-value
Model1500339.57500339.572194.6965<0.0001
Error5913450.623227.97666
Total60513790.2
Simple Linear Regression
4c6df102-f4d5-47a8-a82c-57256f265872-185807_d2l_snhumlpJun 13, 20193KB6
Simple Linear Regression4c6df102-f4d5-47a8-a82c-57256f265872-185807_d2l_snhumlpJun 13, 2019174B5

Simple linear regression results:


Dependent Variable: Textbook Not Used
Independent Variable: Jobs
Textbook Not Used = 0.84632642 - 0.18339877 Jobs
Sample size: 290
R (correlation coefficient) = -0.10642388
R-sq = 0.011326043
Estimate of error standard deviation: 0.96963865

Parameter estimates:


ParameterEstimateStd. Err.AlternativeDFT-StatP-value
Intercept0.846326420.11139763 ≠ 02887.5973464<0.0001
Slope-0.183398770.1009689 ≠ 0288-1.81638870.0704

Analysis of variance table for regression model:


SourceDFSSMSF-statP-value
Model13.10196883.10196883.2992680.0704
Error288270.777340.9401991
Total289273.87931
Simple Linear Regression - Jobs (x) and Textbooks (y)
Assignment 2
sriggsmolinaJun 13, 20193KB9

Simple linear regression results:


Dependent Variable: Received
Independent Variable: Sent
Received = 2.0489195 + 1.0101939 Sent
Sample size: 20
R (correlation coefficient) = 0.99983471
R-sq = 0.99966944
Estimate of error standard deviation: 1.555987

Parameter estimates:


ParameterEstimateStd. Err.AlternativeDFT-StatP-value
Intercept2.04891950.39719337 ≠ 0185.1584938<0.0001
Slope1.01019390.0043297807 ≠ 018233.31295<0.0001

Analysis of variance table for regression model:


SourceDFSSMSF-statP-value
Model1131792.17131792.1754434.933<0.0001
Error1843.5797192.4210955
Total19131835.75
Simple Linear Regression Q21
rachelelamJun 12, 20193KB10

Simple linear regression results:


Dependent Variable: Miles per Gallon, y
Independent Variable: Weight (pounds), x
Miles per Gallon, y = 44.209306 - 0.0069057282 Weight (pounds), x
Sample size: 11
R (correlation coefficient) = -0.95962632
R-sq = 0.92088267
Estimate of error standard deviation: 0.93074958

Parameter estimates:


ParameterEstimateStd. Err.AlternativeDFT-StatP-value
Intercept44.2093062.2232496 ≠ 0919.884994<0.0001
Slope-0.00690572820.00067471735 ≠ 09-10.234994<0.0001

Analysis of variance table for regression model:


SourceDFSSMSF-statP-value
Model190.74880190.748801104.75511<0.0001
Error97.79665310.86629479
Total1098.545455
Simple Linear Regression
4d92114d-52f9-496f-9cb7-c1d1dbdcd91a-145917_d2l_snhumlpJun 12, 20193KB6
Simple Linear Regression
Hours slept prior to working; y axis vs Hours slept when not working; x axis.
kelliernJun 12, 2019174B5

Simple linear regression results:


Dependent Variable: Speed
Independent Variable: Height
Speed = 26.325924 + 0.23801482 Height
Sample size: 200
R (correlation coefficient) = 0.87383235
R-sq = 0.76358298
Estimate of error standard deviation: 9.6281148

Parameter estimates:


ParameterEstimateStd. Err.AlternativeDFT-StatP-value
Intercept26.3259241.360732 ≠ 019819.346885<0.0001
Slope0.238014820.0094120158 ≠ 019825.288399<0.0001

Analysis of variance table for regression model:


SourceDFSSMSF-statP-value
Model159282.32259282.322639.50315<0.0001
Error19818354.71892.700595
Total19977637.04
Height vs Speed Simple Linear Regression
#s for Height vs Speed Linear Regression Slide
a.free2Jun 12, 20193KB7
Simple Linear Regression plottedkatharrellJun 11, 2019174B10

Simple linear regression results:


Dependent Variable: "Selling Price"
Independent Variable: "Square Footage"
"Selling Price" = 14.874048 + 0.15631188 "Square Footage"
Sample size: 12
R (correlation coefficient) = 0.90256596
R-sq = 0.81462531
Estimate of error standard deviation: 69.481514

Parameter estimates:


ParameterEstimateStd. Err.AlternativeDFT-StatP-value
Intercept14.87404863.361184 ≠ 0100.234750150.8191
Slope0.156311880.023579699 ≠ 0106.6290872<0.0001

Analysis of variance table for regression model:


SourceDFSSMSF-statP-value
Model1212151.45212151.4543.944797<0.0001
Error1048276.8084827.6808
Total11260428.26
Simple Linear Regression results share
katharrellJun 11, 20193KB7

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