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Name/Notes Owner Created Size Views
Two sample T summary hypothesis test:
μ1 : Mean of Population 1
μ2 : Mean of Population 2
μ1 - μ2 : Difference between two means
H0 : μ1 - μ2 = 0
HA : μ1 - μ2 ≠ 0
(with pooled variances)

Hypothesis test results:
DifferenceSample Diff.Std. Err.DFT-StatP-value
μ1 - μ2-0.26480.22018549135-1.20262240.2312
Two sample T summary hypothesis test
lidanaulo@gmail.comNov 23, 20171KB0
Two sample T summary hypothesis test:
μ1 : Mean of Population 1
μ2 : Mean of Population 2
μ1 - μ2 : Difference between two means
H0 : μ1 - μ2 = 0
HA : μ1 - μ2 ≠ 0
(without pooled variances)

Hypothesis test results:
DifferenceSample Diff.Std. Err.DFT-StatP-value
μ1 - μ2-0.26480.2243503896.557453-1.18029660.2408
Two sample T summary hypothesis test
lidanaulo@gmail.comNov 23, 20171KB1
Histogram-succesjamondshine@my.lonestar.eduNov 23, 2017174B2
Histogram-success_of_4jamondshine@my.lonestar.eduNov 23, 2017174B2
New column, Sample(evwork), added to data table!
Sample Variable 2 Project 4
jilliankinman139@gmail.comNov 23, 201752B1
New column, Sample1(wrkstat), added to data table!
New column, Sample2(wrkstat), added to data table!
New column, Sample3(wrkstat), added to data table!
New column, Sample4(wrkstat), added to data table!
New column, Sample5(wrkstat), added to data table!
New column, Sample6(wrkstat), added to data table!
New column, Sample7(wrkstat), added to data table!
New column, Sample8(wrkstat), added to data table!
New column, Sample9(wrkstat), added to data table!
New column, Sample10(wrkstat), added to data table!
Project 4 Variable Samples
jilliankinman139@gmail.comNov 23, 2017541B2
Simple linear regression results:
Dependent Variable: Hours Spent Commuting
Independent Variable: Hours Worked per week
Hours Spent Commuting = 20.221381 - 0.10622974 Hours Worked per week
Sample size: 40
R (correlation coefficient) = -0.091322535
R-sq = 0.0083398053
Estimate of error standard deviation: 11.032254

Parameter estimates:
ParameterEstimateStd. Err.AlternativeDFT-StatP-value
Intercept20.2213813.5862674 ≠ 0385.6385592<0.0001
Slope-0.106229740.18791342 ≠ 038-0.565312140.5752

Analysis of variance table for regression model:
SourceDFSSMSF-statP-value
Model138.89601838.8960180.319577820.5752
Error384625.004121.71063
Total394663.9
Hours Spent Commuting & Hours Worked Per WeekSimple Linear Regression
sadecasey@yahoo.comNov 22, 20173KB2
Simple linear regression results:
Dependent Variable: Hours Spent Commuting
Independent Variable: Age
Hours Spent Commuting = 8.5462146 + 0.42505517 Age
Sample size: 40
R (correlation coefficient) = 0.30213093
R-sq = 0.091283102
Estimate of error standard deviation: 10.560807

Parameter estimates:
ParameterEstimateStd. Err.AlternativeDFT-StatP-value
Intercept8.54621465.3370184 ≠ 0381.60130880.1176
Slope0.425055170.21755677 ≠ 0381.95376660.0581

Analysis of variance table for regression model:
SourceDFSSMSF-statP-value
Model1425.73526425.735263.81720410.0581
Error384238.1647111.53065
Total394663.9
Age & Hours Spent Commuting Simple Linear Regression
sadecasey@yahoo.comNov 22, 20173KB2
Simple linear regression results:
Dependent Variable: Hours Worked per week
Independent Variable: Age
Hours Worked per week = 18.356943 - 0.072186386 Age
Sample size: 40
R (correlation coefficient) = -0.059686119
R-sq = 0.0035624328
Estimate of error standard deviation: 9.5069173

Parameter estimates:
ParameterEstimateStd. Err.AlternativeDFT-StatP-value
Intercept18.3569434.8044237 ≠ 0383.82084180.0005
Slope-0.0721863860.19584623 ≠ 038-0.368587070.7145

Analysis of variance table for regression model:
SourceDFSSMSF-statP-value
Model112.27890412.2789040.135856430.7145
Error383434.496190.381476
Total393446.775
Age & Hours Worked Per Week Simple Linear Regression
sadecasey@yahoo.comNov 22, 20173KB4
Analysis of Variance results:
Responses: total score (4 Qs)
Factors: Gender (0=female, 1=male)

Response statistics by factor
Gender (0=female, 1=male)nMeanStd. Dev.Std. Error
0792.41772151.10485640.12430605
1522.73076920.909974890.12619081

ANOVA table
SourceDFSSMSF-StatP-value
Gender (0=female, 1=male)13.07312493.07312492.88428350.0919
Error129137.445961.0654726
Total130140.51908
One Way ANOVA Q's+gender
joshbateman54Nov 22, 20172KB1
Two sample T hypothesis test:
μ1 : Mean of Number of Twitter Followers where Gender = Male
μ2 : Mean of Number of Twitter Followers where Gender = Female
μ1 - μ2 : Difference between two means
H0 : μ1 - μ2 = 0
HA : μ1 - μ2 ≠ 0
(without pooled variances)

Hypothesis test results:
DifferenceSample Diff.Std. Err.DFT-StatP-value
μ1 - μ2-178.88382.37547.433257-0.467813010.6421
Two sample T hypothesis test
49468275_ecollege_msumlpNov 22, 20171KB2
Two sample T confidence interval:
μ1 : Mean of Number of Twitter Followers where Gender = Male
μ2 : Mean of Number of Twitter Followers where Gender = Female
μ1 - μ2 : Difference between two means
(without pooled variances)

95% confidence interval results:
DifferenceSample Diff.Std. Err.DFL. LimitU. Limit
μ1 - μ2-178.88382.37547.433257-947.93385590.17385
Two sample T confidence interval
49468275_ecollege_msumlpNov 22, 20171KB1
One sample proportion summary confidence interval:
p : Proportion of successes
Method: Standard-Wald

90% confidence interval results:
ProportionCountTotalSample Prop.Std. Err.L. LimitU. Limit
p2104000.5250.024968730.483930090.56606991
laurenharrigan
lharrigan1@my.brookdlaecc.eduNov 22, 2017969B2
One sample T summary confidence interval:
μ : Mean of population

95% confidence interval results:
MeanSample MeanStd. Err.DFL. LimitU. Limit
μ112524.59674841056.70851193.2915
laurenharrigan
lharrigan1@my.brookdlaecc.eduNov 22, 2017828B2
laurenharriganlharrigan1@my.brookdlaecc.eduNov 22, 2017174B2

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