Chi-Square Goodness-of-Fit Test for Categorical ... riable: CASE TYPE 1
Observed and Expected Counts
CategoryObservedTest
Proportion
ExpectedContribution
to Chi-Square
Medical Malpractice870.61209.0750
Personal Injury1130.48013.6125
Chi-Square Test
NN*DFChi-SqP-Value
2000122.68750.000
Chart of Observed and Expected Values
One-Sample T: PAY RATE
Descriptive Statistics
NMeanStDevSE Mean95% CI for μ
92265.2118.112.3(240.8, 289.7)
μ: mean of PAY RATE
Test
Null hypothesisH₀: μ = 250
Alternative hypothesisH₁: μ ≠ 250
T-ValueP-Value
1.240.220
One-Sample T: PAY RATE
Descriptive Statistics
NMeanStDevSE Mean95% CI for μ
92265.2118.112.3(240.8, 289.7)
μ: mean of PAY RATE
Test
Null hypothesisH₀: μ = 250
Alternative hypothesisH₁: μ ≠ 250
T-ValueP-Value
1.240.220
Tabulated Statistics: ATTORNEY, CASE TYPE 2
Rows: ATTORNEY   Columns: CASE TYPE 2
CriminalCivilAll
       
Black7426100
  52.5047.50 
  2.967-3.120 
       
Smith3169100
  52.5047.50 
  -2.9673.120 
       
All10595200
Cell Contents
      Count
      Expected count
      Standardized residual
Chi-Square Test
Chi-SquareDFP-Value
Pearson37.07310.000
Likelihood Ratio38.32710.000
Cramer's Measure of Association
Cramer’s V-square0.185363
One-way ANOVA: HOURS versus OUTCOME
Method
Null hypothesisAll means are equal
Alternative hypothesisNot all means are equal
Significance levelα = 0.05
Equal variances were assumed for the analysis.
Factor Information
FactorLevelsValues
OUTCOME3Plea Deal, Conviction, Acquittal
Analysis of Variance
SourceDFAdj SSAdj MSF-ValueP-Value
OUTCOME223841192.1255.240.000
Error57123021.58   
Total593614     
Model Summary
SR-sqR-sq(adj)R-sq(pred)
4.6455065.97%64.77%62.29%
Means
OUTCOMENMeanStDev95% CI
Plea Deal2015.1003.684(13.020, 17.180)
Conviction2029.755.29(27.67, 31.83)
Acquittal2026.654.82(24.57, 28.73)
Pooled StDev = 4.64550
Tukey Pairwise Comparisons
Grouping Information Using the Tukey Method and 95% Confidence
OUTCOMENMeanGrouping
Conviction2029.75A 
Acquittal2026.65A 
Plea Deal2015.100  B
Means that do not share a letter are significantly different.
Interval Plot of HOURS vs OUTCOME
Two-Sample T-Test and CI: B, S & A, T, F, & T
Method
μ₁: mean of B, S & A
µ₂: mean of T, F, & T
Difference: μ₁ - µ₂
Equal variances are assumed for this analysis.
Descriptive Statistics
SampleNMeanStDevSE Mean
B, S & A307.531.590.29
T, F, & T307.371.770.32
Estimation for Difference
DifferencePooled
StDev
95% CI for
Difference
0.1671.684(-0.704, 1.037)
Test
Null hypothesisH₀: μ₁ - µ₂ = 0
Alternative hypothesisH₁: μ₁ - µ₂ ≠ 0
T-ValueDFP-Value
0.38580.703
Power and Sample Size
1-Sample Z Test
Testing mean = null (versus ≠ null)
Calculating power for mean = null + difference
α = 0.05  Assumed standard deviation = 0.08
Results
DifferenceSample
Size
Power
0.04120.409968
Power Curve for 1-Sample Z Test
Power and Sample Size
1-Sample Z Test
Testing mean = null (versus ≠ null)
Calculating power for mean = null + difference
α = 0.05  Assumed standard deviation = 0.08
Results
DifferenceSample
Size
Target
Power
Actual Power
0.04320.80.807430
Power Curve for 1-Sample Z Test
Power and Sample Size
1-Sample Z Test
Testing mean = null (versus ≠ null)
Calculating power for mean = null + difference
α = 0.05  Assumed standard deviation = 0.08
Results
Sample
Size
PowerDifference
120.80.0646998
Power Curve for 1-Sample Z Test