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Author

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R Software Module

rwasp_surveyscores.wasp

Title produced by software

Survey Scores

Date of computation

Mon, 15 Dec 2014 10:25:50 +0000

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/15/t1418639284e74gqzfdxtll8yw.htm/, Retrieved Tue, 10 Feb 2026 13:22:16 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=268031, Retrieved Tue, 10 Feb 2026 13:22:16 +0000

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Estimated Impact

312

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-     [Paired and Unpaired Two Samples Tests about the Mean] [] [2010-11-01 13:07:12] [b98453cac15ba1066b407e146608df68]
- RMP   [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-21 07:47:40] [32b17a345b130fdf5cc88718ed94a974]
- RMPD      [Survey Scores] [] [2014-12-15 10:25:50] [f11ff77f11120bba23ccca75f7c5b5e0] [Current]
- RM          [Survey Scores] [] [2014-12-15 10:28:15] [fda96889f4ef6d31c0c28fd64d281011] 
- RM D        [Harrell-Davis Quantiles] [] [2014-12-15 10:41:06] [fda96889f4ef6d31c0c28fd64d281011] 
- RM D        [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [] [2014-12-15 10:54:59] [fda96889f4ef6d31c0c28fd64d281011] 
- RM D          [Multiple Regression] [] [2014-12-15 15:28:43] [fda96889f4ef6d31c0c28fd64d281011] 
- RM D          [Central Tendency] [] [2014-12-15 19:34:05] [fda96889f4ef6d31c0c28fd64d281011] 

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Dataseries X:

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4 5 1 2 3 4 4 5 4 4 1 1 4 4 4 4 2 1 1 1 2 1 1 4 1 2 4 1 4 4 5 1 2 1 1
2 5 2 3 1 4 5 5 3 3 1 2 2 2 4 5 2 2 2 2 3 2 4 2 2 4 4 2 5 2 5 4 4 2 1
4 4 1 3 2 3 4 4 3 4 2 2 2 2 3 4 2 2 2 2 2 2 4 3 3 4 3 3 4 3 4 4 4 2 2
4 3 2 3 3 4 2 4 5 4 4 3 5 3 2 3 4 3 4 2 4 2 4 4 2 4 4 5 1 4 3 2 3 2 4
3 5 2 4 1 2 4 5 1 1 2 1 2 3 4 5 2 2 2 1 2 2 2 2 2 5 3 4 4 3 4 3 4 3 2
4 3 2 3 2 4 3 4 2 2 3 3 3 3 3 2 3 3 3 3 2 2 2 2 2 3 4 3 3 3 3 3 3 3 3
4 4 2 2 2 4 4 4 4 4 2 4 2 2 4 4 2 2 2 2 2 2 4 3 4 2 3 2 4 3 4 4 2 3 2
4 4 4 4 2 4 4 4 4 4 2 2 4 4 4 4 4 2 3 2 4 3 4 4 3 4 4 4 4 4 4 4 4 3 2
2 3 2 2 2 2 3 3 2 2 1 2 3 3 3 3 3 4 3 2 2 2 2 3 2 3 3 2 3 3 3 3 2 3 2
4 4 3 1 4 3 3 4 2 3 2 2 3 3 4 4 4 2 3 2 3 2 2 2 2 4 4 2 4 4 3 4 4 2 2
5 5 2 4 2 2 4 5 2 4 1 1 1 4 5 2 2 1 3 1 2 1 1 5 2 4 4 4 4 4 5 5 5 3 1
2 2 2 2 2 4 2 4 4 2 2 2 2 2 4 4 2 2 2 1 1 2 1 2 1 2 4 2 2 2 2 2 2 2 1
4 2 2 4 2 4 3 4 2 4 2 2 4 3 4 4 4 2 2 2 2 4 2 3 2 4 4 2 3 4 2 2 3 2 2
4 4 2 2 2 4 4 4 3 2 2 3 4 4 2 4 2 2 2 2 2 2 1 3 2 2 2 2 4 2 4 2 3 2 2
1 4 1 2 1 4 4 4 2 4 2 2 1 4 3 4 3 1 4 2 2 1 4 4 3 4 4 4 4 3 4 3 2 2 1
5 4 2 4 2 4 5 5 4 2 3 2 5 4 5 5 2 2 0 4 4 3 1 5 2 4 4 2 5 4 5 4 4 2 2
4 4 5 3 4 4 2 4 4 4 4 5 5 4 3 4 4 4 3 3 3 5 4 4 3 4 4 2 4 4 4 2 4 3 4
3 2 1 4 2 4 4 4 4 4 2 2 2 3 4 4 1 4 2 1 1 2 2 3 4 4 4 3 4 2 3 2 2 2 1
4 4 3 3 2 4 4 4 4 2 2 3 3 3 4 4 3 2 3 1 1 3 3 3 2 3 3 3 3 3 4 3 3 4 3
2 4 3 4 3 4 4 4 3 4 2 3 2 2 3 4 3 3 2 1 4 2 3 3 3 4 3 2 4 3 4 3 3 3 3
3 1 1 4 2 5 4 4 2 4 2 2 4 4 4 5 4 2 4 3 4 2 3 5 3 3 2 2 5 5 4 3 4 1 1
4 2 4 2 2 4 4 3 4 4 2 3 4 4 5 4 4 2 2 2 2 3 2 5 1 5 4 4 4 3 2 2 3 1 1
4 4 3 3 3 4 4 4 4 3 2 4 4 3 3 4 2 2 2 2 3 3 2 3 2 4 3 2 4 3 4 4 4 2 2
2 2 2 4 2 4 4 4 3 5 4 1 3 4 4 4 4 2 4 3 5 2 3 5 3 2 5 4 3 4 3 5 3 3 2
4 4 3 4 3 4 4 4 4 4 3 3 3 4 3 4 4 3 3 3 4 3 4 4 3 4 5 2 4 4 4 3 3 3 3
4 5 3 1 3 4 5 5 4 4 3 3 4 4 4 5 3 3 4 3 4 4 4 4 3 5 4 4 5 4 5 3 3 3 3
2 2 2 2 2 4 3 4 3 4 2 2 4 4 3 4 2 2 2 2 2 2 2 3 2 4 4 3 2 2 2 2 2 2 2
2 4 2 4 4 4 2 4 2 4 2 2 2 3 4 4 2 2 2 2 2 2 2 4 2 4 2 2 4 4 4 4 4 2 4
4 4 1 2 2 4 4 4 2 3 2 2 3 2 4 4 3 2 2 1 1 2 2 3 2 3 2 3 4 3 4 2 2 1 1
4 2 2 2 3 4 4 4 4 1 1 1 1 2 4 5 1 1 1 1 1 1 1 2 1 2 1 1 3 1 2 2 2 1 1
4 4 4 3 2 2 4 4 4 4 3 4 4 2 3 4 2 4 2 2 2 2 2 2 2 4 3 2 3 2 4 2 3 2 4
2 4 2 5 3 5 3 3 5 2 3 1 2 5 5 3 5 5 3 4 4 1 4 2 1 1 5 1 3 4 3 1 1 1 5
3 4 3 2 2 2 3 4 4 4 2 2 2 2 4 4 2 2 2 2 2 2 2 3 2 3 2 2 3 3 4 3 2 2 2
5 4 5 5 5 5 4 4 5 3 3 2 5 2 3 5 2 5 3 2 4 3 1 5 2 2 4 2 4 4 3 2 2 2 4
2 4 4 5 2 5 2 4 4 4 2 2 1 2 3 4 4 2 2 4 4 1 4 4 2 4 3 2 3 4 3 2 2 2 2
3 4 2 2 1 2 4 4 2 4 2 2 2 2 2 4 4 1 4 2 2 2 2 2 2 4 1 2 4 2 4 2 4 2 2
5 5 2 4 2 4 4 5 4 4 4 2 4 4 4 4 3 1 4 2 2 2 1 4 2 2 2 2 4 3 4 2 2 3 1
4 4 2 4 1 2 4 4 4 2 2 2 2 2 3 4 4 1 3 3 4 4 2 3 3 3 4 2 4 2 4 2 2 3 2
3 4 2 3 2 4 4 4 4 4 3 2 3 3 4 4 3 2 2 2 3 2 2 3 2 4 3 4 4 4 4 4 3 3 2
2 5 1 3 2 5 4 5 2 4 4 1 1 4 3 4 4 1 4 4 2 3 3 3 4 2 5 4 3 4 3 2 3 3 1
2 3 1 2 2 3 4 4 3 2 1 1 3 2 4 4 1 1 1 1 1 1 1 2 1 2 1 2 3 2 3 2 1 2 1
2 4 2 2 2 4 4 4 4 2 2 2 2 2 4 4 2 2 2 2 2 2 2 4 2 4 2 2 2 2 4 4 4 4 2
5 4 5 4 5 5 5 5 5 2 3 2 4 4 5 5 4 3 2 2 4 2 3 5 4 1 5 2 5 5 5 2 3 3 0
2 4 1 1 2 2 4 4 4 2 1 1 2 2 4 4 1 1 1 1 1 2 1 2 2 2 1 1 3 1 4 1 1 2 1
2 5 2 4 3 4 3 4 3 4 2 3 2 3 3 4 2 3 3 3 4 2 2 3 2 3 4 2 3 2 3 4 4 2 3
5 5 3 3 2 5 3 5 4 4 2 2 3 3 4 4 3 2 2 2 4 2 2 3 3 2 3 2 4 3 4 2 3 2 2
2 4 1 2 2 4 3 4 2 3 2 1 2 2 4 4 3 1 2 2 2 1 2 4 2 4 3 2 4 3 4 2 2 2 1
3 4 1 2 1 3 4 4 4 2 2 2 2 2 3 4 2 2 2 2 2 2 1 3 2 3 4 2 4 4 4 4 4 2 2
5 5 3 5 5 5 5 5 4 5 5 4 4 5 4 5 5 3 5 3 5 4 5 5 5 4 5 5 5 4 5 2 2 5 5
3 4 2 4 3 3 4 4 4 4 4 2 2 2 4 4 3 2 4 3 5 2 2 4 2 4 4 4 4 4 4 4 5 3 2
2 2 2 4 2 2 4 5 2 3 2 1 1 3 4 5 2 1 4 1 4 1 1 5 2 2 4 2 4 3 4 2 2 3 1
2 4 2 3 4 4 3 4 2 3 4 2 3 2 3 4 4 3 4 4 2 2 2 2 3 3 3 3 3 2 2 4 3 2 2
1 3 1 1 1 2 2 2 3 3 1 3 1 1 3 4 1 1 1 1 1 1 1 2 1 3 3 2 3 2 2 2 2 1 2
4 5 1 3 3 4 4 4 4 3 2 3 2 4 4 5 3 4 2 1 2 1 3 4 2 4 3 2 5 3 4 2 4 2 3
2 2 2 1 4 5 4 2 2 2 1 1 1 5 5 2 4 1 1 1 4 1 2 5 2 3 5 1 1 5 2 1 2 3 1
4 5 2 4 2 4 5 5 2 3 4 1 2 2 2 5 4 1 4 2 3 2 4 2 4 5 4 4 4 4 5 2 4 4 1
4 5 3 2 2 4 4 5 4 4 2 4 4 4 4 4 3 2 4 2 1 2 1 3 2 4 4 2 4 3 5 2 2 4 2
2 4 1 2 2 4 4 4 2 3 2 2 2 2 4 4 1 1 1 1 1 2 1 4 2 4 2 5 4 4 4 4 4 2 2
3 4 1 2 3 2 4 4 2 3 2 2 1 2 4 4 2 2 2 2 2 1 2 3 2 2 4 2 4 4 4 2 2 2 2
4 3 4 4 2 4 4 4 4 4 2 2 2 3 3 4 2 2 4 1 3 2 2 3 2 2 4 3 4 2 4 3 4 2 0
2 4 2 2 2 4 3 4 3 4 2 1 2 2 4 4 3 1 2 2 2 1 2 4 4 2 3 2 4 4 3 2 2 2 1
3 5 3 2 1 4 4 5 5 4 1 1 2 2 3 4 3 1 3 2 4 1 3 4 2 4 2 3 4 4 4 3 5 2 1
5 5 3 5 4 5 3 5 4 4 3 2 3 4 4 5 5 3 4 4 5 3 3 3 3 4 3 4 4 4 4 3 4 5 1
2 4 1 2 2 2 3 4 3 2 2 1 2 2 4 3 1 1 2 1 2 1 1 3 1 2 3 2 3 3 4 3 2 2 1
4 4 4 3 2 3 4 4 4 3 2 2 3 4 3 4 4 3 3 3 4 2 2 3 3 3 2 4 3 4 4 3 3 2 2
3 4 1 2 1 3 4 3 3 4 1 2 1 2 2 3 1 2 1 1 1 1 1 3 1 2 3 3 3 2 3 2 2 2 2
2 4 2 2 2 4 5 5 2 2 2 2 3 4 4 5 4 3 2 3 3 2 2 3 3 4 2 3 4 3 5 4 4 2 2
4 5 1 3 1 4 5 5 2 4 3 2 1 4 4 4 3 1 3 3 4 1 4 4 3 4 4 5 5 4 5 4 3 2 1
4 2 1 4 5 3 3 4 5 1 2 4 2 2 3 3 1 1 4 2 1 2 2 3 2 3 2 2 2 4 2 1 2 1 1
2 4 1 4 1 3 4 5 1 1 1 1 1 1 3 4 1 1 1 1 1 1 1 1 1 2 1 2 4 1 4 1 1 1 1
4 5 2 2 2 4 5 5 4 4 2 2 2 2 4 4 3 2 2 3 4 2 4 5 3 4 4 4 4 4 5 4 2 2 2
4 5 4 2 2 4 4 4 4 3 2 2 3 4 4 3 4 4 2 2 2 1 2 3 3 4 4 1 4 3 4 4 2 2 2
3 4 2 2 2 3 4 4 4 3 2 2 2 2 4 4 2 2 2 2 2 2 2 4 2 2 4 3 4 4 4 2 2 2 2
3 5 2 4 2 4 4 4 3 4 4 2 2 2 2 4 2 2 3 3 4 3 3 4 2 2 2 4 3 4 4 4 4 4 2
4 4 2 3 2 4 1 3 5 4 2 1 1 4 4 1 1 1 1 1 4 1 1 4 1 4 1 4 2 2 1 3 4 2 1
4 4 3 2 2 4 3 4 4 2 2 3 2 3 4 4 2 2 3 2 2 1 2 4 2 3 4 2 3 4 4 4 3 1 1
3 4 3 3 2 5 4 4 2 4 2 1 4 3 2 4 3 1 2 2 3 1 4 3 2 4 2 4 3 4 3 3 4 1 1
3 4 2 4 2 4 4 4 4 3 2 2 3 4 4 4 5 2 3 2 3 2 3 4 3 3 4 3 4 4 4 3 2 2 2
4 4 2 3 2 2 4 5 4 1 1 4 3 3 4 4 2 1 1 1 3 1 2 3 2 4 4 2 4 4 5 3 2 2 1
3 5 1 3 1 3 4 4 2 3 1 1 1 2 3 4 2 1 1 1 2 1 1 4 1 4 3 3 3 2 4 3 4 1 1
2 5 1 2 1 4 5 5 2 1 1 1 1 2 4 1 1 1 1 1 5 1 1 4 1 1 4 1 5 2 5 2 2 1 1
3 3 2 4 1 4 4 4 1 3 2 1 2 3 4 4 3 1 2 1 3 1 3 4 2 3 3 3 4 4 3 3 3 2 1
2 4 1 3 1 3 3 4 3 2 2 1 2 3 3 4 2 1 1 3 1 1 2 2 1 2 2 2 4 2 4 2 2 3 1
2 4 1 2 2 5 5 5 5 2 2 2 2 3 5 5 4 1 3 2 2 2 3 3 4 2 4 2 5 3 5 2 2 2 2
3 2 3 3 4 3 2 4 4 1 2 2 3 3 2 3 3 2 3 2 2 3 1 3 1 2 4 1 3 3 2 3 2 2 2
1 2 3 3 3 4 3 2 3 4 3 3 2 3 4 4 3 4 3 3 4 4 4 3 4 3 2 4 3 4 4 3 3 3 3
3 4 1 3 2 4 3 4 4 2 2 3 2 3 4 4 2 3 2 2 2 2 2 3 2 3 3 2 3 3 4 2 3 2 2
4 4 2 2 2 4 4 4 2 2 2 2 2 1 4 4 2 1 2 1 1 2 2 2 1 2 4 1 3 4 4 2 2 2 2
4 5 2 4 2 4 5 5 4 2 3 4 4 5 3 5 5 5 2 2 5 4 3 5 2 4 4 4 5 3 5 2 4 2 5
4 4 3 2 1 2 4 4 4 2 2 4 2 1 3 4 2 2 2 1 3 1 2 1 2 2 4 2 4 2 4 3 3 2 1
4 4 1 4 1 3 3 4 5 3 2 1 3 2 4 4 4 1 3 2 4 1 3 4 3 3 3 4 3 3 3 4 4 2 1
2 4 2 3 2 3 4 4 4 3 2 2 2 2 3 4 2 2 2 2 2 2 2 2 2 3 3 2 3 3 4 2 2 2 2
5 2 2 4 2 4 2 3 4 4 4 2 3 4 2 3 4 4 4 3 4 3 2 4 2 4 4 5 2 4 2 4 4 4 4
4 4 3 3 2 4 4 4 4 3 2 2 2 2 4 4 2 1 2 2 2 2 2 4 2 3 4 2 4 3 5 3 2 2 2
3 3 2 3 2 3 3 3 4 2 1 3 2 2 4 3 2 2 1 2 2 2 2 2 1 2 3 2 2 2 3 2 3 2 2
2 4 1 2 1 3 4 4 2 3 3 2 3 3 4 4 2 1 2 1 3 2 2 3 2 2 4 2 4 2 4 2 2 3 2
4 4 1 2 2 3 4 4 4 2 2 4 3 2 3 4 2 3 2 2 2 2 2 2 2 3 2 2 3 2 4 2 2 2 3
4 3 1 4 2 4 4 4 2 4 2 2 2 2 4 4 2 2 2 2 2 1 1 3 1 4 3 2 4 3 3 4 4 3 2
2 2 1 3 2 4 2 3 2 2 2 2 2 3 3 3 3 2 2 2 2 1 2 4 2 4 3 4 3 3 3 2 2 2 2
4 3 1 3 3 4 4 4 1 4 4 2 2 3 4 4 2 2 4 2 4 1 1 2 2 5 3 4 3 3 4 2 2 3 2
4 5 3 3 3 4 5 5 4 4 2 2 3 4 4 5 4 4 2 3 4 3 3 4 3 4 4 3 5 3 5 2 5 4 2
4 4 4 3 3 4 4 5 5 3 3 3 2 2 4 4 3 3 4 3 2 2 3 4 3 2 3 2 4 3 4 2 2 4 3
2 3 2 2 2 3 4 4 4 3 2 2 2 2 2 4 2 3 2 2 2 2 2 2 2 4 2 2 3 2 3 2 2 2 2
4 4 2 3 2 3 4 3 3 5 4 2 2 1 4 4 2 2 4 4 4 4 2 3 2 4 2 2 4 4 3 4 3 4 2
2 4 2 4 1 4 4 5 2 2 2 2 2 4 2 4 2 1 1 1 3 1 2 4 2 2 4 2 2 4 4 4 4 1 1
4 4 3 3 4 4 4 4 2 2 3 4 3 2 4 4 4 3 4 2 4 4 3 3 4 3 4 2 4 3 4 2 2 1 1
3 5 3 4 3 3 3 5 2 3 2 2 2 3 3 3 3 2 3 3 3 2 3 4 3 3 2 3 3 4 3 3 5 1 2
4 4 2 3 2 4 3 4 4 4 2 2 4 4 3 3 3 2 2 3 4 2 3 3 3 2 3 2 3 4 4 3 3 3 2
2 4 1 2 1 4 5 4 1 2 2 1 1 2 4 5 1 1 2 2 2 1 1 2 1 2 2 3 4 2 4 3 4 2 1
3 4 2 3 1 5 4 4 4 4 2 2 2 3 4 4 4 1 3 2 3 2 3 4 3 2 4 3 4 4 4 3 2 3 1
2 4 1 3 1 4 5 4 2 3 2 1 1 4 4 4 2 1 4 2 4 1 4 2 4 4 5 5 5 4 5 1 2 2 2

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 seconds
R Server	'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 3 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268031&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268031&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268031&T=0

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 seconds
R Server	'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

Summary of survey scores (median of Likert score was subtracted)
Question	mean	Sum ofpositives (Ps)	Sum ofnegatives (Ns)	(Ps-Ns)/(Ps+Ns)	Count ofpositives (Pc)	Count ofnegatives (Nc)	(Pc-Nc)/(Pc+Nc)
1	0.21	62	39	0.23	53	36	0.19
2	0.84	109	16	0.74	85	15	0.7
3	-0.88	14	112	-0.78	11	79	-0.76
4	-0.05	40	46	-0.07	35	41	-0.08
5	-0.79	16	104	-0.73	12	82	-0.74
6	0.68	89	14	0.73	76	14	0.69
7	0.74	93	11	0.79	78	10	0.77
8	1.12	127	3	0.95	99	3	0.94
9	0.25	69	41	0.25	59	36	0.24
10	0.07	51	43	0.09	48	36	0.14
11	-0.76	14	98	-0.75	13	82	-0.73
12	-0.86	13	109	-0.79	12	83	-0.75
13	-0.52	25	83	-0.54	21	66	-0.52
14	-0.14	38	53	-0.16	34	48	-0.17
15	0.58	75	11	0.74	68	11	0.72
16	0.94	111	7	0.88	93	5	0.9
17	-0.28	36	67	-0.3	31	54	-0.27
18	-0.95	15	120	-0.78	12	82	-0.74
19	-0.52	24	82	-0.55	23	64	-0.47
20	-0.94	7	111	-0.88	7	82	-0.84
21	-0.26	43	72	-0.25	37	57	-0.21
22	-1.04	10	125	-0.85	9	89	-0.82
23	-0.7	19	97	-0.67	18	72	-0.6
24	0.29	59	27	0.37	47	25	0.31
25	-0.74	12	94	-0.77	11	75	-0.74
26	0.14	55	39	0.17	50	36	0.16
27	0.26	62	33	0.31	54	27	0.33
28	-0.35	34	73	-0.36	28	64	-0.39
29	0.6	79	12	0.74	66	10	0.74
30	0.19	52	31	0.25	49	28	0.27
31	0.74	95	13	0.76	76	12	0.73
32	-0.28	30	61	-0.34	28	54	-0.32
33	-0.13	40	54	-0.15	35	50	-0.18
34	-0.69	13	90	-0.75	11	74	-0.74
35	-1.11	12	135	-0.84	9	92	-0.82

\begin{tabular}{lllllllll}
\hline
Summary of survey scores (median of Likert score was subtracted) \tabularnewline
Question & mean & Sum ofpositives (Ps) & Sum ofnegatives (Ns) & (Ps-Ns)/(Ps+Ns) & Count ofpositives (Pc) & Count ofnegatives (Nc) & (Pc-Nc)/(Pc+Nc) \tabularnewline
1 & 0.21 & 62 & 39 & 0.23 & 53 & 36 & 0.19 \tabularnewline
2 & 0.84 & 109 & 16 & 0.74 & 85 & 15 & 0.7 \tabularnewline
3 & -0.88 & 14 & 112 & -0.78 & 11 & 79 & -0.76 \tabularnewline
4 & -0.05 & 40 & 46 & -0.07 & 35 & 41 & -0.08 \tabularnewline
5 & -0.79 & 16 & 104 & -0.73 & 12 & 82 & -0.74 \tabularnewline
6 & 0.68 & 89 & 14 & 0.73 & 76 & 14 & 0.69 \tabularnewline
7 & 0.74 & 93 & 11 & 0.79 & 78 & 10 & 0.77 \tabularnewline
8 & 1.12 & 127 & 3 & 0.95 & 99 & 3 & 0.94 \tabularnewline
9 & 0.25 & 69 & 41 & 0.25 & 59 & 36 & 0.24 \tabularnewline
10 & 0.07 & 51 & 43 & 0.09 & 48 & 36 & 0.14 \tabularnewline
11 & -0.76 & 14 & 98 & -0.75 & 13 & 82 & -0.73 \tabularnewline
12 & -0.86 & 13 & 109 & -0.79 & 12 & 83 & -0.75 \tabularnewline
13 & -0.52 & 25 & 83 & -0.54 & 21 & 66 & -0.52 \tabularnewline
14 & -0.14 & 38 & 53 & -0.16 & 34 & 48 & -0.17 \tabularnewline
15 & 0.58 & 75 & 11 & 0.74 & 68 & 11 & 0.72 \tabularnewline
16 & 0.94 & 111 & 7 & 0.88 & 93 & 5 & 0.9 \tabularnewline
17 & -0.28 & 36 & 67 & -0.3 & 31 & 54 & -0.27 \tabularnewline
18 & -0.95 & 15 & 120 & -0.78 & 12 & 82 & -0.74 \tabularnewline
19 & -0.52 & 24 & 82 & -0.55 & 23 & 64 & -0.47 \tabularnewline
20 & -0.94 & 7 & 111 & -0.88 & 7 & 82 & -0.84 \tabularnewline
21 & -0.26 & 43 & 72 & -0.25 & 37 & 57 & -0.21 \tabularnewline
22 & -1.04 & 10 & 125 & -0.85 & 9 & 89 & -0.82 \tabularnewline
23 & -0.7 & 19 & 97 & -0.67 & 18 & 72 & -0.6 \tabularnewline
24 & 0.29 & 59 & 27 & 0.37 & 47 & 25 & 0.31 \tabularnewline
25 & -0.74 & 12 & 94 & -0.77 & 11 & 75 & -0.74 \tabularnewline
26 & 0.14 & 55 & 39 & 0.17 & 50 & 36 & 0.16 \tabularnewline
27 & 0.26 & 62 & 33 & 0.31 & 54 & 27 & 0.33 \tabularnewline
28 & -0.35 & 34 & 73 & -0.36 & 28 & 64 & -0.39 \tabularnewline
29 & 0.6 & 79 & 12 & 0.74 & 66 & 10 & 0.74 \tabularnewline
30 & 0.19 & 52 & 31 & 0.25 & 49 & 28 & 0.27 \tabularnewline
31 & 0.74 & 95 & 13 & 0.76 & 76 & 12 & 0.73 \tabularnewline
32 & -0.28 & 30 & 61 & -0.34 & 28 & 54 & -0.32 \tabularnewline
33 & -0.13 & 40 & 54 & -0.15 & 35 & 50 & -0.18 \tabularnewline
34 & -0.69 & 13 & 90 & -0.75 & 11 & 74 & -0.74 \tabularnewline
35 & -1.11 & 12 & 135 & -0.84 & 9 & 92 & -0.82 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268031&T=1

[TABLE]
[ROW][C]Summary of survey scores (median of Likert score was subtracted)[/C][/ROW]
[ROW][C]Question[/C][C]mean[/C][C]Sum ofpositives (Ps)[/C][C]Sum ofnegatives (Ns)[/C][C](Ps-Ns)/(Ps+Ns)[/C][C]Count ofpositives (Pc)[/C][C]Count ofnegatives (Nc)[/C][C](Pc-Nc)/(Pc+Nc)[/C][/ROW]
[ROW][C]1[/C][C]0.21[/C][C]62[/C][C]39[/C][C]0.23[/C][C]53[/C][C]36[/C][C]0.19[/C][/ROW]
[ROW][C]2[/C][C]0.84[/C][C]109[/C][C]16[/C][C]0.74[/C][C]85[/C][C]15[/C][C]0.7[/C][/ROW]
[ROW][C]3[/C][C]-0.88[/C][C]14[/C][C]112[/C][C]-0.78[/C][C]11[/C][C]79[/C][C]-0.76[/C][/ROW]
[ROW][C]4[/C][C]-0.05[/C][C]40[/C][C]46[/C][C]-0.07[/C][C]35[/C][C]41[/C][C]-0.08[/C][/ROW]
[ROW][C]5[/C][C]-0.79[/C][C]16[/C][C]104[/C][C]-0.73[/C][C]12[/C][C]82[/C][C]-0.74[/C][/ROW]
[ROW][C]6[/C][C]0.68[/C][C]89[/C][C]14[/C][C]0.73[/C][C]76[/C][C]14[/C][C]0.69[/C][/ROW]
[ROW][C]7[/C][C]0.74[/C][C]93[/C][C]11[/C][C]0.79[/C][C]78[/C][C]10[/C][C]0.77[/C][/ROW]
[ROW][C]8[/C][C]1.12[/C][C]127[/C][C]3[/C][C]0.95[/C][C]99[/C][C]3[/C][C]0.94[/C][/ROW]
[ROW][C]9[/C][C]0.25[/C][C]69[/C][C]41[/C][C]0.25[/C][C]59[/C][C]36[/C][C]0.24[/C][/ROW]
[ROW][C]10[/C][C]0.07[/C][C]51[/C][C]43[/C][C]0.09[/C][C]48[/C][C]36[/C][C]0.14[/C][/ROW]
[ROW][C]11[/C][C]-0.76[/C][C]14[/C][C]98[/C][C]-0.75[/C][C]13[/C][C]82[/C][C]-0.73[/C][/ROW]
[ROW][C]12[/C][C]-0.86[/C][C]13[/C][C]109[/C][C]-0.79[/C][C]12[/C][C]83[/C][C]-0.75[/C][/ROW]
[ROW][C]13[/C][C]-0.52[/C][C]25[/C][C]83[/C][C]-0.54[/C][C]21[/C][C]66[/C][C]-0.52[/C][/ROW]
[ROW][C]14[/C][C]-0.14[/C][C]38[/C][C]53[/C][C]-0.16[/C][C]34[/C][C]48[/C][C]-0.17[/C][/ROW]
[ROW][C]15[/C][C]0.58[/C][C]75[/C][C]11[/C][C]0.74[/C][C]68[/C][C]11[/C][C]0.72[/C][/ROW]
[ROW][C]16[/C][C]0.94[/C][C]111[/C][C]7[/C][C]0.88[/C][C]93[/C][C]5[/C][C]0.9[/C][/ROW]
[ROW][C]17[/C][C]-0.28[/C][C]36[/C][C]67[/C][C]-0.3[/C][C]31[/C][C]54[/C][C]-0.27[/C][/ROW]
[ROW][C]18[/C][C]-0.95[/C][C]15[/C][C]120[/C][C]-0.78[/C][C]12[/C][C]82[/C][C]-0.74[/C][/ROW]
[ROW][C]19[/C][C]-0.52[/C][C]24[/C][C]82[/C][C]-0.55[/C][C]23[/C][C]64[/C][C]-0.47[/C][/ROW]
[ROW][C]20[/C][C]-0.94[/C][C]7[/C][C]111[/C][C]-0.88[/C][C]7[/C][C]82[/C][C]-0.84[/C][/ROW]
[ROW][C]21[/C][C]-0.26[/C][C]43[/C][C]72[/C][C]-0.25[/C][C]37[/C][C]57[/C][C]-0.21[/C][/ROW]
[ROW][C]22[/C][C]-1.04[/C][C]10[/C][C]125[/C][C]-0.85[/C][C]9[/C][C]89[/C][C]-0.82[/C][/ROW]
[ROW][C]23[/C][C]-0.7[/C][C]19[/C][C]97[/C][C]-0.67[/C][C]18[/C][C]72[/C][C]-0.6[/C][/ROW]
[ROW][C]24[/C][C]0.29[/C][C]59[/C][C]27[/C][C]0.37[/C][C]47[/C][C]25[/C][C]0.31[/C][/ROW]
[ROW][C]25[/C][C]-0.74[/C][C]12[/C][C]94[/C][C]-0.77[/C][C]11[/C][C]75[/C][C]-0.74[/C][/ROW]
[ROW][C]26[/C][C]0.14[/C][C]55[/C][C]39[/C][C]0.17[/C][C]50[/C][C]36[/C][C]0.16[/C][/ROW]
[ROW][C]27[/C][C]0.26[/C][C]62[/C][C]33[/C][C]0.31[/C][C]54[/C][C]27[/C][C]0.33[/C][/ROW]
[ROW][C]28[/C][C]-0.35[/C][C]34[/C][C]73[/C][C]-0.36[/C][C]28[/C][C]64[/C][C]-0.39[/C][/ROW]
[ROW][C]29[/C][C]0.6[/C][C]79[/C][C]12[/C][C]0.74[/C][C]66[/C][C]10[/C][C]0.74[/C][/ROW]
[ROW][C]30[/C][C]0.19[/C][C]52[/C][C]31[/C][C]0.25[/C][C]49[/C][C]28[/C][C]0.27[/C][/ROW]
[ROW][C]31[/C][C]0.74[/C][C]95[/C][C]13[/C][C]0.76[/C][C]76[/C][C]12[/C][C]0.73[/C][/ROW]
[ROW][C]32[/C][C]-0.28[/C][C]30[/C][C]61[/C][C]-0.34[/C][C]28[/C][C]54[/C][C]-0.32[/C][/ROW]
[ROW][C]33[/C][C]-0.13[/C][C]40[/C][C]54[/C][C]-0.15[/C][C]35[/C][C]50[/C][C]-0.18[/C][/ROW]
[ROW][C]34[/C][C]-0.69[/C][C]13[/C][C]90[/C][C]-0.75[/C][C]11[/C][C]74[/C][C]-0.74[/C][/ROW]
[ROW][C]35[/C][C]-1.11[/C][C]12[/C][C]135[/C][C]-0.84[/C][C]9[/C][C]92[/C][C]-0.82[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268031&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268031&T=1

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Summary of survey scores (median of Likert score was subtracted)
Question	mean	Sum ofpositives (Ps)	Sum ofnegatives (Ns)	(Ps-Ns)/(Ps+Ns)	Count ofpositives (Pc)	Count ofnegatives (Nc)	(Pc-Nc)/(Pc+Nc)
1	0.21	62	39	0.23	53	36	0.19
2	0.84	109	16	0.74	85	15	0.7
3	-0.88	14	112	-0.78	11	79	-0.76
4	-0.05	40	46	-0.07	35	41	-0.08
5	-0.79	16	104	-0.73	12	82	-0.74
6	0.68	89	14	0.73	76	14	0.69
7	0.74	93	11	0.79	78	10	0.77
8	1.12	127	3	0.95	99	3	0.94
9	0.25	69	41	0.25	59	36	0.24
10	0.07	51	43	0.09	48	36	0.14
11	-0.76	14	98	-0.75	13	82	-0.73
12	-0.86	13	109	-0.79	12	83	-0.75
13	-0.52	25	83	-0.54	21	66	-0.52
14	-0.14	38	53	-0.16	34	48	-0.17
15	0.58	75	11	0.74	68	11	0.72
16	0.94	111	7	0.88	93	5	0.9
17	-0.28	36	67	-0.3	31	54	-0.27
18	-0.95	15	120	-0.78	12	82	-0.74
19	-0.52	24	82	-0.55	23	64	-0.47
20	-0.94	7	111	-0.88	7	82	-0.84
21	-0.26	43	72	-0.25	37	57	-0.21
22	-1.04	10	125	-0.85	9	89	-0.82
23	-0.7	19	97	-0.67	18	72	-0.6
24	0.29	59	27	0.37	47	25	0.31
25	-0.74	12	94	-0.77	11	75	-0.74
26	0.14	55	39	0.17	50	36	0.16
27	0.26	62	33	0.31	54	27	0.33
28	-0.35	34	73	-0.36	28	64	-0.39
29	0.6	79	12	0.74	66	10	0.74
30	0.19	52	31	0.25	49	28	0.27
31	0.74	95	13	0.76	76	12	0.73
32	-0.28	30	61	-0.34	28	54	-0.32
33	-0.13	40	54	-0.15	35	50	-0.18
34	-0.69	13	90	-0.75	11	74	-0.74
35	-1.11	12	135	-0.84	9	92	-0.82

Pearson correlations of survey scores (and p-values)
	mean	(Ps-Ns)/(Ps+Ns)	(Pc-Nc)/(Pc+Nc)
mean	1 (0)	0.992 (0)	0.991 (0)
(Ps-Ns)/(Ps+Ns)	0.992 (0)	1 (0)	0.999 (0)
(Pc-Nc)/(Pc+Nc)	0.991 (0)	0.999 (0)	1 (0)

\begin{tabular}{lllllllll}
\hline
Pearson correlations of survey scores (and p-values) \tabularnewline
 & mean & (Ps-Ns)/(Ps+Ns) & (Pc-Nc)/(Pc+Nc) \tabularnewline
mean & 1 (0) & 0.992 (0) & 0.991 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.992 (0) & 1 (0) & 0.999 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.991 (0) & 0.999 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268031&T=2

[TABLE]
[ROW][C]Pearson correlations of survey scores (and p-values)[/C][/ROW]
[ROW][C][/C][C]mean[/C][C](Ps-Ns)/(Ps+Ns)[/C][C](Pc-Nc)/(Pc+Nc)[/C][/ROW]
[ROW][C]mean[/C][C]1 (0)[/C][C]0.992 (0)[/C][C]0.991 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.992 (0)[/C][C]1 (0)[/C][C]0.999 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.991 (0)[/C][C]0.999 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268031&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268031&T=2

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Pearson correlations of survey scores (and p-values)
	mean	(Ps-Ns)/(Ps+Ns)	(Pc-Nc)/(Pc+Nc)
mean	1 (0)	0.992 (0)	0.991 (0)
(Ps-Ns)/(Ps+Ns)	0.992 (0)	1 (0)	0.999 (0)
(Pc-Nc)/(Pc+Nc)	0.991 (0)	0.999 (0)	1 (0)

Kendall tau rank correlations of survey scores (and p-values)
	mean	(Ps-Ns)/(Ps+Ns)	(Pc-Nc)/(Pc+Nc)
mean	1 (0)	0.938 (0)	0.927 (0)
(Ps-Ns)/(Ps+Ns)	0.938 (0)	1 (0)	0.969 (0)
(Pc-Nc)/(Pc+Nc)	0.927 (0)	0.969 (0)	1 (0)

\begin{tabular}{lllllllll}
\hline
Kendall tau rank correlations of survey scores (and p-values) \tabularnewline
 & mean & (Ps-Ns)/(Ps+Ns) & (Pc-Nc)/(Pc+Nc) \tabularnewline
mean & 1 (0) & 0.938 (0) & 0.927 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.938 (0) & 1 (0) & 0.969 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.927 (0) & 0.969 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268031&T=3

[TABLE]
[ROW][C]Kendall tau rank correlations of survey scores (and p-values)[/C][/ROW]
[ROW][C][/C][C]mean[/C][C](Ps-Ns)/(Ps+Ns)[/C][C](Pc-Nc)/(Pc+Nc)[/C][/ROW]
[ROW][C]mean[/C][C]1 (0)[/C][C]0.938 (0)[/C][C]0.927 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.938 (0)[/C][C]1 (0)[/C][C]0.969 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.927 (0)[/C][C]0.969 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268031&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268031&T=3

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Kendall tau rank correlations of survey scores (and p-values)
	mean	(Ps-Ns)/(Ps+Ns)	(Pc-Nc)/(Pc+Nc)
mean	1 (0)	0.938 (0)	0.927 (0)
(Ps-Ns)/(Ps+Ns)	0.938 (0)	1 (0)	0.969 (0)
(Pc-Nc)/(Pc+Nc)	0.927 (0)	0.969 (0)	1 (0)

Parameters (Session):

par1 = 1 2 3 4 5 6 7 ;

Parameters (R input):

par1 = 1 2 3 4 5 ;

R code (references can be found in the software module):

par1 <- '1 2 3 4 5'
docor <- function(x,y,method) {
r <- cor.test(x,y,method=method)
paste(round(r$estimate,3),' (',round(r$p.value,3),')',sep='')
}
x <- t(x)
nx <- length(x[,1])
cx <- length(x[1,])
mymedian <- median(as.numeric(strsplit(par1,' ')[[1]]))
myresult <- array(NA, dim = c(cx,7))
rownames(myresult) <- paste('Q',1:cx,sep='')
colnames(myresult) <- c('mean','Sum of
positives (Ps)','Sum of
negatives (Ns)', '(Ps-Ns)/(Ps+Ns)', 'Count of
positives (Pc)', 'Count of
negatives (Nc)', '(Pc-Nc)/(Pc+Nc)')
for (i in 1:cx) {
spos <- 0
sneg <- 0
cpos <- 0
cneg <- 0
for (j in 1:nx) {
if (!is.na(x[j,i])) {
myx <- as.numeric(x[j,i]) - mymedian
if (myx > 0) {
spos = spos + myx
cpos = cpos + 1
}
if (myx < 0) {
sneg = sneg + abs(myx)
cneg = cneg + 1
}
}
}
myresult[i,1] <- round(mean(as.numeric(x[,i]),na.rm=T)-mymedian,2)
myresult[i,2] <- spos
myresult[i,3] <- sneg
myresult[i,4] <- round((spos - sneg) / (spos + sneg),2)
myresult[i,5] <- cpos
myresult[i,6] <- cneg
myresult[i,7] <- round((cpos - cneg) / (cpos + cneg),2)
}
myresult
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Summary of survey scores (median of Likert score was subtracted)',8,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Question',header=TRUE)
for (i in 1:7) {
a<-table.element(a,colnames(myresult)[i],header=TRUE)
}
a<-table.row.end(a)
for (i in 1:cx) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
for (j in 1:7) {
a<-table.element(a,myresult[i,j],align='right')
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Pearson correlations of survey scores (and p-values)',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',header=TRUE)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,'(Ps-Ns)/(Ps+Ns)',header=TRUE)
a<-table.element(a,'(Pc-Nc)/(Pc+Nc)',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,docor(myresult[,1],myresult[,1],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,1],myresult[,4],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,1],myresult[,7],method='pearson'),align='right')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'(Ps-Ns)/(Ps+Ns)',header=TRUE)
a<-table.element(a,docor(myresult[,4],myresult[,1],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,4],myresult[,4],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,4],myresult[,7],method='pearson'),align='right')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'(Pc-Nc)/(Pc+Nc)',header=TRUE)
a<-table.element(a,docor(myresult[,7],myresult[,1],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,7],myresult[,4],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,7],myresult[,7],method='pearson'),align='right')
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Kendall tau rank correlations of survey scores (and p-values)',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',header=TRUE)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,'(Ps-Ns)/(Ps+Ns)',header=TRUE)
a<-table.element(a,'(Pc-Nc)/(Pc+Nc)',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,docor(myresult[,1],myresult[,1],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,1],myresult[,4],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,1],myresult[,7],method='kendall'),align='right')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'(Ps-Ns)/(Ps+Ns)',header=TRUE)
a<-table.element(a,docor(myresult[,4],myresult[,1],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,4],myresult[,4],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,4],myresult[,7],method='kendall'),align='right')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'(Pc-Nc)/(Pc+Nc)',header=TRUE)
a<-table.element(a,docor(myresult[,7],myresult[,1],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,7],myresult[,4],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,7],myresult[,7],method='kendall'),align='right')
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable2.tab')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code