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Exam Statistics and Results
Table: ceStatsExam
Aggregation of all Item Stats for the Exam.
| Field | Description |
|---|---|
| StatsID | Unique Identifier for this set of Statistics |
| QtyQuestions | Count of all Items on the Exam |
| QtyCandidates | Count of all Candidates taking the Exam |
| QtyCompetencies | Count of distinct Competencies from all Items on the Exam |
| QtySections | Count of Sections on the Exam |
| ValueMax | Maximum achievable points for Exam, from sum of all Value Max of Items on the Exam |
| QtyCorrect | Total of all QtyCorrect for all Items on the Exam |
| QtySkipped | Total of all QtySkipped for all Items on the Exam |
| QtyIncorrect | Total of all QtyIncorrect for all Items on the Exam |
| RawPercent | x = Count of Correct Items on Exam n = Count of Candidates on Exam k = Count of Items on Exam x/(n*k*100)  graphic |
| ValueCorrect | Total of all ValueCorrect for all Items on the Exam |
| ValueSkipped | Total of all ValueSkipped for all Items on the Exam |
| ValueIncorrect | Total of all ValueIncorrect for all Items on the Exam |
| ValueTotal | (ValueCorrect + ValueSkipped + ValueIncorrect) |
| ValuePercent | ValueTotal/(ValueMax*100) graphic |
| Difficulty | x = Count of Correct Items on Exam n = Count of Candidates on Exam k = Count of Items on Exam x/(n*k) graphic |
| RawHigh | Highest QtyCorrect achieved by a Candidate on the Exam |
| RawLow | Lowest QtyCorrect achieved by a Candidate on the Exam |
| RawMean | Mean (average) QtyCorrect achieved by a Candidate on the Exam |
| RawVariance | Variance of QtyCorrect for all Candidates on the Exam |
| RawStdev | Standard Deviation of QtyCorrect for all Candidates on the Exam |
| ValueHigh | Highest ValueTotal achieved by a Candidate on the Exam |
ValueStdev Standard Deviation of ValueTotal for all Candidates on the Exam ValueMedian Median (middle) ValueTotal for all Candidates on the Exam ValueMode Mode (most frequent) ValueTotal for all Candidates on the Exam PercentDistribution Text field which holds a summary of the score distributions. Not a statistic, but used in reporting QtyPassExam Count of Candidates that passed Exam. See Candidate Statistics (PassExam) SpearmanBrown (2*SpearmanRank)/1) KuderRichardson20 k = Count of Items on Exam Total Test Variance = Variance of Candidate Raw Scores Sum of p*q = sum of all items p (difficulty) * q (1-p) for all items in Exam
k/2)*3)/(Total Test Variance) KuderRichardson21 qtyX = Count Items answered correctly on Exam x ̅ = Mean of QtyCorrect for each Candidate on Exam s = StDev of Raw Scores of all Candidates on Exam
qtyX/4)* 5))/6) StandardError s = StDev of QtyCorrect for Exam n = Count of Candidates s/√n AlphaCoefficient k = Count of Items on Exam Total Test Variance = Variance of Candidate Raw Scores Sum of Item Variance = Sum of all item variances on Exam
k/7)*8)/(Total Test Variance) SpearmanRank n = Number of Candidates RankOdd = Candidates Ranking on Odd Items only compared to all other Candidates on Exam RankEven = Candidates Ranking on Odd Items only compared to all other Candidates on Exam
1- (6*∑▒(RankOdd-RankEven)^2 )/(n*(n^2-1)) Skewness n = Count of Candidates xi = QtyCorrect for each Candidate on Exam x ̅ = Mean of QtyCorrect on Exam s = StDev of QtyCorrect on Exam n/9) ∑▒10)/√(n* (n-1))
Kurtosis n = Count of Candidates xi = QtyCorrect for each Candidate on Exam x ̅ = Mean of QtyCorrect for Exam s = StDev of QtyCorrect for Exam
Calculate Sample Kurtosis KurtS (n(n+1) ∑▒(x_i- x ̅ ) ^4)/11)/12)-6)/13)
AlternateSystem Stores Alternate Value used for Calculation (True, Custom, ZScore, TScore,…) see Alternate Scores
AlternateBase Alternate Base used in Alternate Calculations see Alternate Scores
AlternateMean Alternate Mean used in Alternate Calculations see Alternate Scores
AlternateStDev Alternate Standard Deviation used in Alternate Calculations see Alternate Scores
QuestionLogitSum Future use QuestionLogitMean Future use QuestionLogitVariance Future use QuestionLogitSquaredSum Future use QuestionSpreadExpansion Future use CandidateLogitSum Future use CandidateLogitMean Future use CandidateLogitVariance Future use CandidateLogitSquaredSum Future use CandidateSpreadExpansion Future use
