Component Translated Unfinished Unfinished words Unfinished characters Untranslated Checks Suggestions Comments
jaspAcceptanceSampling-QML GPL-2.0 41% 866 2,515 17,274 791 5 2 0
jaspAcceptanceSampling-R GPL-2.0 68% 174 1,547 9,931 168 3 0 0
jaspAnova-QML GPL-2.0 58% 2,692 7,393 49,650 2,278 251 2 0
jaspAnova-R GPL-2.0 77% 949 6,460 43,551 752 179 2 1
jaspAudit-QML GPL-2.0 35% 6,732 67,802 441,546 6,476 34 2 0
jaspAudit-R GPL-2.0 49% 2,676 33,312 217,564 2,521 40 14 0
jaspBain-QML GPL-3.0 46% 1,129 4,300 27,959 1,008 14 0 0
jaspBain-R GPL-3.0 82% 133 1,726 11,025 126 11 0 0
jaspBase AGPL-3.0 78% 99 1,181 7,786 97 2 0 1
jaspBFF-QML GPL-2.0 23% 600 1,438 8,808 598 3 0 1
jaspBFF-R GPL-2.0 47% 52 278 1,896 52 0 0 0
jaspBsts-QML GPL-2.0 43% 512 1,372 9,939 511 0 2 0
jaspBsts-R GPL-2.0 78% 49 167 1,132 49 9 22 0
jaspCircular-QML GPL-2.0 56% 333 684 4,893 331 13 1 0
jaspCircular-R GPL-2.0 76% 83 757 4,678 83 8 0 0
jaspCochrane-QML GPL-2.0 48% 519 1,000 7,014 519 20 1 0
jaspCochrane-R GPL-2.0 85% 30 178 1,143 30 0 0 0
jaspDescriptives-QML GPL-2.0 44% 4,155 46,039 287,368 3,918 40 4 3
jaspDescriptives-R GPL-2.0 62% 888 5,682 36,365 801 24 1 3
jaspDesktop AGPL-3.0 65% 7,551 46,824 277,954 7,301 159 5 10
jaspDistributions-QML AGPL-3.0 52% 6,331 18,726 133,181 6,272 77 1 1
jaspDistributions-R AGPL-3.0 67% 747 4,808 34,632 736 23 0 0
jaspEquivalenceTTests-QML AGPL-3.0 55% 925 2,111 14,645 886 46 6 0
jaspEquivalenceTTests-R AGPL-3.0 90% 49 165 1,186 42 9 2 0
jaspFactor-QML GPL-2.0 57% 1,344 2,671 18,721 1,305 18 41 0
jaspFactor-R GPL-2.0 84% 321 2,045 13,444 233 72 0 0
jaspFrequencies-QML GPL-2.0 61% 2,048 5,414 35,916 1,742 103 0 0
jaspFrequencies-R GPL-2.0 74% 599 3,411 22,618 441 42 1 3
jaspGraphs GPL-2.0 86% 51 298 2,015 47 0 0 0
jaspJags-QML AGPL-3.0 51% 743 1,600 10,574 738 20 3 0
jaspJags-R AGPL-3.0 83% 76 567 3,349 69 10 0 0
jaspLearnBayes-QML AGPL-3.0 45% 2,897 5,665 37,390 2,841 21 1 0
jaspLearnBayes-R AGPL-3.0 66% 938 16,266 113,512 885 30 0 0
jaspLearnStats-QML GPL-2.0 42% 3,096 6,474 43,661 2,961 88 1 0
jaspLearnStats-R GPL-2.0 71% 235 1,430 8,896 235 4 0 1
jaspMachineLearning-QML AGPL-3.0 47% 5,916 50,251 319,463 5,396 164 4 1
jaspMachineLearning-R AGPL-3.0 58% 1,873 8,394 55,300 1,783 56 0 0
jaspMetaAnalysis-QML AGPL-3.0 27% 13,850 65,118 451,107 13,062 94 2 0
jaspMetaAnalysis-R GPL-2.0 55% 1,919 10,942 73,842 1,724 73 0 0
jaspMixedModels-QML AGPL-3.0 57% 1,481 2,868 21,571 1,470 50 1 0
jaspMixedModels-R GPL-2.0 77% 329 4,522 29,749 314 54 0 0
jaspNetwork-QML AGPL-3.0 48% 2,058 3,843 25,012 1,979 41 1 0
jaspNetwork-R GPL-2.0 85% 76 600 3,936 69 10 0 0
jaspPower-QML GPL-2.0 54% 445 1,018 5,132 440 22 3 0
jaspPower-R GPL-2.0 75% 242 4,439 26,089 238 6 0 3
jaspPredictiveAnalytics-QML GPL-2.0 28% 1,455 4,607 30,820 1,440 16 1 0
jaspPredictiveAnalytics-R 80% 36 948 6,063 34 2 0 0
jaspProcess-QML GPL-2.0 24% 2,261 3,786 28,622 2,243 28 0 0
jaspProcess-R GPL-2.0 61% 92 536 3,642 82 1 0 0
jaspProphet-QML AGPL-3.0 57% 574 1,206 9,717 573 6 2 0
jaspProphet-R GPL-2.0 78% 121 843 5,571 119 19 0 0
jaspQualityControl-QML GPL-2.0 31% 8,984 21,324 141,349 8,554 72 8 1
jaspQualityControl-R GPL-2.0 38% 1,955 8,593 55,343 1,433 47 0 0
jaspRegression-QML AGPL-3.0 53% 3,782 7,543 54,136 3,252 119 11 0
jaspRegression-R GPL-2.0 65% 1,728 9,213 62,511 1,390 234 7 3
jaspReliability-QML AGPL-3.0 37% 1,993 4,653 32,808 1,689 44 0 0
jaspReliability-R GPL-2.0 62% 472 2,877 20,014 411 64 13 0
jaspRobustTTests-QML 23% 1,282 2,479 18,930 1,278 1 0 0
jaspRobustTTests-R GPL-2.0 61% 76 280 1,973 71 4 0 0
jaspSem-QML AGPL-3.0 44% 2,678 5,716 42,372 2,485 40 0 0
jaspSem-R GPL-2.0 66% 927 4,202 29,389 754 98 1 0
jaspSummaryStatistics-QML AGPL-3.0 52% 1,580 3,707 22,742 1,486 38 0 0
jaspSummaryStatistics-R GPL-2.0 65% 344 2,573 16,323 337 10 0 3
jaspTestModule-R (do not translate) AGPL-3.0 28% 35 152 881 35 0 0 0
jaspTimeSeries-QML GPL-2.0 39% 1,893 13,659 84,540 1,852 10 0 0
jaspTimeSeries-R GPL-2.0 74% 111 434 2,900 111 7 0 0
jaspTTests-QML GPL-2.0 60% 1,224 2,896 20,271 1,077 51 171 6
jaspTTests-R AGPL-3.0 66% 743 5,100 33,010 686 45 2 1
jaspVisualModeling-QML AGPL-3.0 54% 788 1,516 10,341 747 8 1 0
jaspVisualModeling-R GPL-2.0 0 0 0 0 0 0 0
Glossary JASP GPL-2.0 67% 1,423 2,194 15,411 1,404 0 15 1

Overview

Project website jasp-stats.org
Project maintainers User avatar JASPStats
2 minutes ago

String statistics

Strings percent Hosted strings Words percent Hosted words Characters percent Hosted characters
Total 236,176 1,093,822 7,206,103
Source 17,435 81,769 540,186
Translated 51% 120,808 48% 528,484 48% 3,484,007
Needs editing 3% 7,507 2% 22,290 2% 150,571
Read-only 7% 17,004 7% 81,108 7% 535,088
Failing checks 1% 2,912 1% 10,405 1% 71,711
Strings with suggestions 1% 357 1% 1,238 1% 9,420
Untranslated strings 45% 107,861 49% 543,048 49% 3,571,525
Last 12 months Previous

Activity in last 12 months

42,978 changes 27,897 changes 55,803 changes 38,957 changes 40,811 changes 27,819 changes 22,149 changes 29,479 changes 19,085 changes 31,608 changes 39,147 changes 37,742 changes 38,641 changes 42,809 changes 18,242 changes 45,643 changes 34,613 changes 31,760 changes 17,037 changes 27,042 changes 16,075 changes 30,463 changes 31,345 changes 33,815 changes
Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct

Quick numbers

1,095 k
Hosted words
236 k
Hosted strings
51%
Translated
12
Contributors
and previous 30 days

Trends of last 30 days

+8%
Hosted words
+100%
+8%
Hosted strings
+100%
−2%
Translated
+54%
−8%
Contributors
+100%
User avatar None

Resource updated
The “po/QML-zh_Hant.po” file was changed. 2 minutes ago
User avatar None

String added in the repository
When the auditor has information that indicates a low-risk profile on the population, they can use this information to reduce their required sample size via the Audit Risk Model (ARM) provided that there are no errors in the population. According to the ARM, the audit risk (AR) is a function of the inherent risk (IR), the internal control risk (CR), the analytical risk (CAR) and the detection risk (DR).

*AR = IR x CR x CAR x DR*

The auditor assesses inherent risk, internal control risk and analytical risk generally on a 3-point scale consisting of high, medium and low to determine the appropriate detection risk. To use the ARM, these categorical risk assessments must be mapped to probabilities. By default, the Audit module uses the percentages shown in the table below, which are inspired by the <i>Handboek Auditing Rijksoverheid</i>. You can manually adjust the percentages associated with one or all of the risks by selecting the Custom option in the drop-down list under the corresponding risk assessment.

| | Inherent risk (IR) | Control risk (CR) | Analytical risk (CAR) |
| ---: | :---: | :---: | :---: |
| High | 100% | 100% | 100% |
| Medium | 63% | 52% | 50% |
| Low | 40% | 34% | 25% |
 
2 minutes ago
User avatar None

Resource updated
The “po/QML-zh_Hans.po” file was changed. 2 minutes ago
User avatar None

String added in the repository
When the auditor has information that indicates a low-risk profile on the population, they can use this information to reduce their required sample size via the Audit Risk Model (ARM) provided that there are no errors in the population. According to the ARM, the audit risk (AR) is a function of the inherent risk (IR), the internal control risk (CR), the analytical risk (CAR) and the detection risk (DR).

*AR = IR x CR x CAR x DR*

The auditor assesses inherent risk, internal control risk and analytical risk generally on a 3-point scale consisting of high, medium and low to determine the appropriate detection risk. To use the ARM, these categorical risk assessments must be mapped to probabilities. By default, the Audit module uses the percentages shown in the table below, which are inspired by the <i>Handboek Auditing Rijksoverheid</i>. You can manually adjust the percentages associated with one or all of the risks by selecting the Custom option in the drop-down list under the corresponding risk assessment.

| | Inherent risk (IR) | Control risk (CR) | Analytical risk (CAR) |
| ---: | :---: | :---: | :---: |
| High | 100% | 100% | 100% |
| Medium | 63% | 52% | 50% |
| Low | 40% | 34% | 25% |
 
2 minutes ago
User avatar None

Resource updated
The “po/QML-tr.po” file was changed. 2 minutes ago
User avatar None

String added in the repository
When the auditor has information that indicates a low-risk profile on the population, they can use this information to reduce their required sample size via the Audit Risk Model (ARM) provided that there are no errors in the population. According to the ARM, the audit risk (AR) is a function of the inherent risk (IR), the internal control risk (CR), the analytical risk (CAR) and the detection risk (DR).

*AR = IR x CR x CAR x DR*

The auditor assesses inherent risk, internal control risk and analytical risk generally on a 3-point scale consisting of high, medium and low to determine the appropriate detection risk. To use the ARM, these categorical risk assessments must be mapped to probabilities. By default, the Audit module uses the percentages shown in the table below, which are inspired by the <i>Handboek Auditing Rijksoverheid</i>. You can manually adjust the percentages associated with one or all of the risks by selecting the Custom option in the drop-down list under the corresponding risk assessment.

| | Inherent risk (IR) | Control risk (CR) | Analytical risk (CAR) |
| ---: | :---: | :---: | :---: |
| High | 100% | 100% | 100% |
| Medium | 63% | 52% | 50% |
| Low | 40% | 34% | 25% |
 
2 minutes ago
User avatar None

Resource updated
The “po/QML-ru.po” file was changed. 2 minutes ago
User avatar None

String added in the repository
When the auditor has information that indicates a low-risk profile on the population, they can use this information to reduce their required sample size via the Audit Risk Model (ARM) provided that there are no errors in the population. According to the ARM, the audit risk (AR) is a function of the inherent risk (IR), the internal control risk (CR), the analytical risk (CAR) and the detection risk (DR).

*AR = IR x CR x CAR x DR*

The auditor assesses inherent risk, internal control risk and analytical risk generally on a 3-point scale consisting of high, medium and low to determine the appropriate detection risk. To use the ARM, these categorical risk assessments must be mapped to probabilities. By default, the Audit module uses the percentages shown in the table below, which are inspired by the <i>Handboek Auditing Rijksoverheid</i>. You can manually adjust the percentages associated with one or all of the risks by selecting the Custom option in the drop-down list under the corresponding risk assessment.

| | Inherent risk (IR) | Control risk (CR) | Analytical risk (CAR) |
| ---: | :---: | :---: | :---: |
| High | 100% | 100% | 100% |
| Medium | 63% | 52% | 50% |
| Low | 40% | 34% | 25% |
 
2 minutes ago
User avatar None

Resource updated
The “po/QML-pt_BR.po” file was changed. 2 minutes ago
User avatar None

String added in the repository
When the auditor has information that indicates a low-risk profile on the population, they can use this information to reduce their required sample size via the Audit Risk Model (ARM) provided that there are no errors in the population. According to the ARM, the audit risk (AR) is a function of the inherent risk (IR), the internal control risk (CR), the analytical risk (CAR) and the detection risk (DR).

*AR = IR x CR x CAR x DR*

The auditor assesses inherent risk, internal control risk and analytical risk generally on a 3-point scale consisting of high, medium and low to determine the appropriate detection risk. To use the ARM, these categorical risk assessments must be mapped to probabilities. By default, the Audit module uses the percentages shown in the table below, which are inspired by the <i>Handboek Auditing Rijksoverheid</i>. You can manually adjust the percentages associated with one or all of the risks by selecting the Custom option in the drop-down list under the corresponding risk assessment.

| | Inherent risk (IR) | Control risk (CR) | Analytical risk (CAR) |
| ---: | :---: | :---: | :---: |
| High | 100% | 100% | 100% |
| Medium | 63% | 52% | 50% |
| Low | 40% | 34% | 25% |
 
2 minutes ago
Browse all project changes