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Name/Notes Owner Created Size Views
Boxplotapagan93Apr 24, 2018174B0
Two sample proportion summary hypothesis test:
p1 : proportion of successes for population 1
p2 : proportion of successes for population 2
p1 - p2 : Difference in proportions
H0 : p1 - p2 = 0
HA : p1 - p2 ≠ 0

Hypothesis test results:
DifferenceCount1Total1Count2Total2Sample Diff.Std. Err.Z-StatP-value
p1 - p24651881050.0638655460.0594048231.07509030.2823
Two sample proportion summary hypothesis test
winblapaApr 24, 20181KB1
Pie Chart With DatanwvanzeeApr 23, 2018174B0
Two sample T hypothesis test:
μ1 : Mean of Male
μ2 : Mean of Female
μ1 - μ2 : Difference between two means
H0 : μ1 - μ2 = 0
HA : μ1 - μ2 ≠ 0
(without pooled variances)


Sample Statistics:
SamplenMeanStd. dev.
Male20314269.96744
Female20177.5204.22421

Hypothesis test results:
DifferenceSample Diff.Std. Err.DFT-StatP-value
μ1 - μ2136.575.69344335.3812721.80332660.0799
Two sample T hypothesis test
28999116_ecollege_msumlpApr 23, 20182KB4
Two sample T confidence interval:
μ1 : Mean of Male
μ2 : Mean of Female
μ1 - μ2 : Difference between two means
(without pooled variances)


Sample Statistics:
SamplenMeanStd. dev.
Male20314269.96744
Female20177.5204.22421

95% confidence interval results:
DifferenceSample Diff.Std. Err.DFL. LimitU. Limit
μ1 - μ2136.575.69344335.381272-17.106687290.10669
Two sample T confidence interval
28999116_ecollege_msumlpApr 23, 20182KB3
Simple linear regression results:
Dependent Variable: var2
Independent Variable: var1
var2 = 9 + 0 var1
Sample size: 9
R (correlation coefficient) = 0
R-sq = 0
Estimate of error standard deviation: 0.9258201

Parameter estimates:
ParameterEstimateStd. Err.AlternativeDFT-StatP-value
Intercept93.4156503 ≠ 072.63493020.0337
Slope00.37796447 ≠ 0701

Analysis of variance table for regression model:
SourceDFSSMSF-statP-value
Model10001
Error760.85714286
Total86
Simple Linear Regression
dsapkota81Apr 23, 20182KB1
Chi-Square Calculator-Critical value-Z. Marino-Lab 11zkm25Apr 23, 2018174B1
Contingency table results:
Rows: var1
Columns: None

Cell format
Count
(Expected count)

drove when drinkingNo Driving when DrinkingTotal
texted while driving731
(394.74)
3054
(3390.26)
3785
no texting while driving156
(492.26)
4564
(4227.74)
4720
Total88776188505

Chi-Square test:
StatisticDFValueP-value
Chi-square1576.22407<0.0001
Contingency table (with summary)-Lab 11-Z. Marino
zkm25Apr 23, 20182KB1
Simple linear regression results:
Dependent Variable: Height (in)
Independent Variable: Age
Height (in) = 59.522331 + 0.20415558 Age
Sample size: 40
R (correlation coefficient) = 0.43581299
R-sq = 0.18993296
Estimate of error standard deviation: 2.5152568

Parameter estimates:
ParameterEstimateStd. Err.AlternativeDFT-StatP-value
Intercept59.5223311.5762239 ≠ 03837.762611<0.0001
Slope0.204155580.068395851 ≠ 0382.98491170.0049

Analysis of variance table for regression model:
SourceDFSSMSF-statP-value
Model156.36735456.3673548.90969780.0049
Error38240.407656.326517
Total39296.775
Simple Linear Regression Height Age
sortokApr 23, 20183KB1
Simple linear regression results:
Dependent Variable: Height (in)
Independent Variable: Shoe Size
Height (in) = 54.461082 + 1.2305815 Shoe Size
Sample size: 40
R (correlation coefficient) = 0.62618263
R-sq = 0.39210468
Estimate of error standard deviation: 2.1788948

Parameter estimates:
ParameterEstimateStd. Err.AlternativeDFT-StatP-value
Intercept54.4610821.9722021 ≠ 03827.614352<0.0001
Slope1.23058150.24856043 ≠ 0384.9508345<0.0001

Analysis of variance table for regression model:
SourceDFSSMSF-statP-value
Model1116.36687116.3668724.510763<0.0001
Error38180.408134.7475825
Total39296.775
Simple Linear Regression Height Shoe
sortokApr 23, 20183KB2
Simple linear regression results:
Dependent Variable: Age
Independent Variable: Shoe Size
Age = 9.1594957 + 1.6819845 Shoe Size
Sample size: 40
R (correlation coefficient) = 0.40093475
R-sq = 0.16074867
Estimate of error standard deviation: 5.4652093

Parameter estimates:
ParameterEstimateStd. Err.AlternativeDFT-StatP-value
Intercept9.15949574.9467727 ≠ 0381.85161040.0719
Slope1.68198450.62345129 ≠ 0382.69786040.0104

Analysis of variance table for regression model:
SourceDFSSMSF-statP-value
Model1217.3965217.39657.27845080.0104
Error381135.003529.868513
Total391352.4
Simple Linear Regression Age and Shoe Size
sortokApr 23, 20183KB1
Simple linear regression results:
Dependent Variable: Height (in)
Independent Variable: Weight (lbs)
Height (in) = 57.350609 + 0.044334208 Weight (lbs)
Sample size: 40
R (correlation coefficient) = 0.50718832
R-sq = 0.25723999
Estimate of error standard deviation: 2.408497

Parameter estimates:
ParameterEstimateStd. Err.AlternativeDFT-StatP-value
Intercept57.3506091.8923152 ≠ 03830.307112<0.0001
Slope0.0443342080.012220871 ≠ 0383.62774530.0008

Analysis of variance table for regression model:
SourceDFSSMSF-statP-value
Model176.34239876.34239813.1605360.0008
Error38220.43265.8008579
Total39296.775
Simple Linear Regression Height Weight
sortokApr 23, 20183KB1
Simple linear regression results:
Dependent Variable: Age
Independent Variable: Weight (lbs)
Age = 8.0391637 + 0.094022326 Weight (lbs)
Sample size: 40
R (correlation coefficient) = 0.50387447
R-sq = 0.25388948
Estimate of error standard deviation: 5.1530264

Parameter estimates:
ParameterEstimateStd. Err.AlternativeDFT-StatP-value
Intercept8.03916374.0486453 ≠ 0381.98564290.0543
Slope0.0940223260.026146793 ≠ 0383.59594110.0009

Analysis of variance table for regression model:
SourceDFSSMSF-statP-value
Model1343.36013343.3601312.9307920.0009
Error381009.039926.553681
Total391352.4
Simple Linear Regression Age Weight
sortokApr 23, 20183KB1
Simple linear regression results:
Dependent Variable: Height (in)
Independent Variable: Age
Height (in) = 59.522331 + 0.20415558 Age
Sample size: 40
R (correlation coefficient) = 0.43581299
R-sq = 0.18993296
Estimate of error standard deviation: 2.5152568

Parameter estimates:
ParameterEstimateStd. Err.AlternativeDFT-StatP-value
Intercept59.5223311.5762239 ≠ 03837.762611<0.0001
Slope0.204155580.068395851 ≠ 0382.98491170.0049

Analysis of variance table for regression model:
SourceDFSSMSF-statP-value
Model156.36735456.3673548.90969780.0049
Error38240.407656.326517
Total39296.775
Simple Linear Regression Height and Age
sortokApr 23, 20183KB1
Simple linear regression results:
Dependent Variable: Weight (lbs)
Independent Variable: Shoe Size
Weight (lbs) = 34.497031 + 14.99878 Shoe Size
Sample size: 40
R (correlation coefficient) = 0.6671389
R-sq = 0.44507432
Estimate of error standard deviation: 23.81604

Parameter estimates:
ParameterEstimateStd. Err.AlternativeDFT-StatP-value
Intercept34.49703121.556821 ≠ 0381.60028380.1178
Slope14.998782.7168476 ≠ 0385.5206556<0.0001

Analysis of variance table for regression model:
SourceDFSSMSF-statP-value
Model117287.03117287.03130.477638<0.0001
Error3821553.744567.20378
Total3938840.775
Simple Linear Regression Weight and Shoe Size
sortokApr 23, 20183KB1

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