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Simple linear regression results:
Dependent Variable: var2
Independent Variable: var1
var2 = 73.309278 + 3.3762887 var1
Sample size: 10
R (correlation coefficient) = 0.77097409
R-sq = 0.59440104
Estimate of error standard deviation: 6.8671112

Parameter estimates:
ParameterEstimateStd. Err.AlternativeDFT-StatP-value
Intercept73.3092783.2852218 ≠ 0822.314864<0.0001
Slope3.37628870.98605971 ≠ 083.42402050.009

Analysis of variance table for regression model:
SourceDFSSMSF-statP-value
Model1552.86727552.8672711.7239160.009
Error8377.2577347.157216
Total9930.125
Simple Linear Regression
morotd@kean.eduFeb 18, 20183KB3
Simple Linear Regressionjazziepal@gmail.comFeb 16, 2018174B5
Simple linear regression results:
Dependent Variable: Salary (in millions)
Independent Variable: Age
Salary (in millions) = 29.167836 - 0.50474256 Age
Sample size: 15
R (correlation coefficient) = -0.15809561
R-sq = 0.024994221
Estimate of error standard deviation: 11.256075

Parameter estimates:
ParameterEstimateStd. Err.AlternativeDFT-StatP-value
Intercept29.16783623.380582 ≠ 0131.2475240.2342
Slope-0.504742560.87434342 ≠ 013-0.577281820.5736

Analysis of variance table for regression model:
SourceDFSSMSF-statP-value
Model142.22306142.2230610.33325430.5736
Error131647.0899126.69922
Total141689.313
Simple Linear Regression
lazoni@kean.eduFeb 16, 20183KB5
Simple Linear Regressionlazoni@kean.eduFeb 16, 2018174B6
Simple linear regression results:
Dependent Variable: calories
Independent Variable: grams of fat
calories = 106.66667 + 5.3333333 grams of fat
Sample size: 25
R (correlation coefficient) = 0.38441511
R-sq = 0.14777498
Estimate of error standard deviation: 10.848095

Parameter estimates:
ParameterEstimateStd. Err.AlternativeDFT-StatP-value
Intercept106.666674.0939773 ≠ 02326.054533<0.0001
Slope5.33333332.6706163 ≠ 0231.99704210.0578

Analysis of variance table for regression model:
SourceDFSSMSF-statP-value
Model1469.33333469.333333.98817730.0578
Error232706.6667117.68116
Total243176
Simple Linear Regression
47315601_ecollege_msumlpFeb 16, 20183KB4
Simple linear regression results:
Dependent Variable: SYSTOLIC
Independent Variable: BMI
SYSTOLIC = 108.59411 + 0.4968777 BMI
Sample size: 300
R (correlation coefficient) = 0.21147821
R-sq = 0.044723035
Estimate of error standard deviation: 15.519138

Parameter estimates:
ParameterEstimateStd. Err.AlternativeDFT-StatP-value
Intercept108.594113.9491137 ≠ 029827.498349<0.0001
Slope0.49687770.13302718 ≠ 02983.73515920.0002

Analysis of variance table for regression model:
SourceDFSSMSF-statP-value
Model13360.10963360.109613.9514140.0002
Error29871771.41240.84366
Total29975131.52
BMI blood pressure Simple Linear Regression
lwissnerpcFeb 15, 20183KB2
Simple linear regression results:
Dependent Variable: Years at current setting
Independent Variable: Years Practicing
Years at current setting = -1.4987542 + 0.88010757 Years Practicing
Sample size: 124
R (correlation coefficient) = 0.8962687
R-sq = 0.80329757
Estimate of error standard deviation: 4.7405286

Parameter estimates:
ParameterEstimateStd. Err.AlternativeDFT-StatP-value
Intercept-1.49875420.71779786 ≠ 0122-2.08798920.0389
Slope0.880107570.039429609 ≠ 012222.320981<0.0001

Analysis of variance table for regression model:
SourceDFSSMSF-statP-value
Model111196.44411196.444498.22621<0.0001
Error1222741.658522.472611
Total12313938.102
Simple Linear Regression
dmeasterlingFeb 15, 20183KB3
Simple Linear Regression Q 6ajbucki65984Feb 14, 2018174B4
Simple Linear Regressiondryan66602Feb 14, 2018174B3
Simple Linear Regressiondryan66602Feb 14, 2018174B3
Simple Linear Regression Question 6Ampinno65398Feb 14, 2018174B4
Simple Linear RegressionhsamueFeb 14, 2018174B3
Simple linear regression results:
Dependent Variable: Top speed (mph)
Independent Variable: Horsepower
Top speed (mph) = 84.454138 + 0.23870491 Horsepower
Sample size: 82
R (correlation coefficient) = 0.96654517
R-sq = 0.93420956
Estimate of error standard deviation: 3.6230867

Parameter estimates:
ParameterEstimateStd. Err.AlternativeDFT-StatP-value
Intercept84.4541380.92102554 ≠ 08091.695761<0.0001
Slope0.238704910.0070823209 ≠ 08033.704334<0.0001

Analysis of variance table for regression model:
SourceDFSSMSF-statP-value
Model114911.76214911.7621135.9822<0.0001
Error801050.140613.126757
Total8115961.902
Simple Linear Regression: chapter 8, q4
dzemmuhFeb 12, 20183KB5
Simple Linear RegressionhsamueFeb 12, 2018174B5
Simple Linear RegressionhsamueFeb 12, 2018174B6

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