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Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_surveyscores.wasp

Title produced by software

Survey Scores

Date of computation

Mon, 05 Apr 2010 12:47:13 +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/2010/Apr/05/t1270471667mb02yn344mzcneh.htm/, Retrieved Mon, 29 Apr 2024 05:54:47 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=74593, Retrieved Mon, 29 Apr 2024 05:54:47 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

1404

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

-     [Survey Scores] [E-Learn 2008 table 1] [2008-09-07 11:33:54] [b98453cac15ba1066b407e146608df68]
F RM D    [Survey Scores] [ATTLES] [2010-04-05 12:47:13] [d76b387543b13b5e3afd8ff9e5fdc89f] [Current]
F RMPD      [Notched Boxplots] [Compare ATTLES Sc...] [2010-10-03 17:09:07] [b98453cac15ba1066b407e146608df68] 
F             [Notched Boxplots] [Connected en Sepa...] [2010-10-08 13:35:40] [aeb27d5c05332f2e597ad139ee63fbe4] 
F             [Notched Boxplots] [] [2010-10-09 11:52:59] [f3d662049ef6875ba0c96bb458434b66] 
- R             [Notched Boxplots] [workshop 2 Task 6] [2013-10-15 10:22:39] [f661ab64c60045a179a329b9ddab9bfe] 
-             [Notched Boxplots] [] [2010-10-09 11:54:16] [1ad9dd03b6c5806e9fe90049663fcef1] 
-             [Notched Boxplots] [] [2010-10-09 12:16:32] [a9671b130b33f9fcb98554992ce4582f] 
-    D        [Notched Boxplots] [ATTLES Boxplots] [2010-10-09 12:40:47] [6bc4f9343b7ea3ef5a59412d1f72bb2b] 
-             [Notched Boxplots] [Taak 6: connected...] [2010-10-09 18:44:02] [74deae64b71f9d77c839af86f7c687b5] 
-             [Notched Boxplots] [Task 6 probability] [2010-10-10 09:44:09] [87d60b8864dc39f7ed759c345edfb471] 
- R             [Notched Boxplots] [taak 6] [2011-10-10 08:19:29] [c4580079d5d2b3f0ba412f27cdc441be] 
-                 [Notched Boxplots] [taak 6 B] [2011-10-10 08:20:18] [c4580079d5d2b3f0ba412f27cdc441be] 
-             [Notched Boxplots] [Workshop 2 taak 6] [2010-10-11 16:59:13] [1afa3497b02a8d7c9f6727c1b17b89b2] 
-             [Notched Boxplots] [] [2010-10-11 21:00:29] [f4dc4aa51d65be851b8508203d9f6001] 
F             [Notched Boxplots] [work shop 2 task 6] [2010-10-11 22:23:51] [74be16979710d4c4e7c6647856088456] 
F             [Notched Boxplots] [Task 6] [2010-10-11 22:26:13] [48146708a479232c43a8f6e52fbf83b4] 
-             [Notched Boxplots] [Connected Index] [2010-10-12 15:27:17] [abf4ff90b26c6b37be4a30063b404639] 
-             [Notched Boxplots] [] [2010-10-12 20:31:51] [de4adef75375d243bafd27c3fb0ddf4c] 
- RM          [Notched Boxplots] [Workshop 2 - Task 6] [2011-10-06 17:00:30] [fbaf17a8836493f6de0f4e0e997711e1] 
- R           [Notched Boxplots] [] [2011-10-06 21:00:49] [ee8c3a74bf3b349877806e9a50913c60] 
- R           [Notched Boxplots] [Task 6 (ws2)] [2011-10-07 07:56:59] [10b12745961ee885a66356b3bf31ed40] 
- R           [Notched Boxplots] [Workshop 2 taak 6] [2011-10-07 14:57:32] [aa7c7608f809e956d7797134ec926e04] 
- RM          [Notched Boxplots] [] [2011-10-08 13:00:32] [06c08141d7d783218a8164fd2ea166f2] 
- R           [Notched Boxplots] [] [2011-10-08 21:34:56] [a9a952c1cbc7081c25fad93a34aab827] 
- R           [Notched Boxplots] [Task 6] [2011-10-09 12:40:14] [1321c14511baa35aebbc5dda661708fe] 
- R           [Notched Boxplots] [] [2011-10-09 14:22:57] [50e3859e0b739a5118d466e989dfc0cb] 
- RM          [Notched Boxplots] [] [2011-10-09 15:38:13] [90a803f646514fc2f7a5d6de952a552a] 
- R           [Notched Boxplots] [task 6] [2011-10-09 17:26:25] [80bca13c5f9401fbb753952fd2952f4a] 
-               [Notched Boxplots] [Notched boxplots] [2012-12-04 18:42:14] [f8da7216ca6ab56f40bda6dd57b36742] 
- RM          [Notched Boxplots] [] [2011-10-09 17:40:35] [aefb5c2d4042694c5b6b82f93ac1885a] 
- RM          [Notched Boxplots] [task 6] [2011-10-10 12:37:13] [d31984dff2665bea309b726bae3d5241] 
- R           [Notched Boxplots] [task 6] [2011-10-10 12:54:35] [379dab8110dbf77cfcc4b7951c3a599f] 
- RM          [Notched Boxplots] [opdracht 6] [2011-10-10 19:02:18] [8fcdd1f5b88bf5ac5d2a0b8a91219b89] 
- RM          [Notched Boxplots] [] [2011-10-11 08:07:16] [f2efe7b37bd12d7944b0ea184fe3529a] 
- RM          [Notched Boxplots] [Workshop 2 - Task 6] [2011-10-11 08:10:42] [ec29c78521a0445a37e4526edb78f709] 
- RM          [Notched Boxplots] [ws 2 - task 6] [2011-10-11 08:45:26] [7e261c986c934df955dd3ac53e9d45c6] 
- R           [Notched Boxplots] [] [2011-10-11 09:16:26] [ad2d4c5ace9fa07b356a7b5098237581] 
-  M            [Notched Boxplots] [WS2: vraag 6] [2011-10-24 16:16:55] [8ce6c7315af51b5eb6923c5fe455d382] 
-    D          [Notched Boxplots] [] [2011-12-18 12:01:19] [ad2d4c5ace9fa07b356a7b5098237581] 
- R           [Notched Boxplots] [] [2011-10-11 10:17:38] [18e0b15711387f6270134133fa101957] 
- R           [Notched Boxplots] [] [2011-10-11 10:36:11] [72554d79606dc183296fd485368f0ec1] 
- R           [Notched Boxplots] [vraag 6] [2011-10-11 10:41:02] [c505444e07acba7694d29053ca5d114e] 
- R P         [Notched Boxplots] [] [2011-10-11 14:28:04] [86a47bcc75cd2e0d5b5c9888edc893c2] 
- RM          [Notched Boxplots] [WS 2 - Task 6] [2011-10-11 15:04:33] [74b1e5a3104ff0b2404b2865a63336ad] 
- R           [Notched Boxplots] [Workshop 2 - Fabr...] [2011-10-11 15:04:50] [60c0c94f647e2c90e494ab0f2a2f1926] 
- R P         [Notched Boxplots] [] [2011-10-11 15:29:57] [a1957df0bc37aec4aa3c994e6a08412c] 
- RM          [Notched Boxplots] [Workshop 2 Task 6] [2011-10-11 15:40:48] [59e9c089bdd600b584669dddc48fbcc3] 
- RM          [Notched Boxplots] [WS2 Task 6] [2011-10-11 16:12:30] [ab11d59973a0ec4be849e25906c4cdbf] 
- R           [Notched Boxplots] [Notched Boxplots] [2011-10-11 16:19:43] [f7a862281046b7153543b12c78921b36] 

[Truncated]

Feedback Forum

2010-04-11 19:26:30 [8326296a4a969e220946fc6855491489] [reply] 
Question 1 : In evaluating what someone says, I focus on the quality of their argument, not on the person who's p... 
Question 2 : I like playing devil's advocate - arguing the opposite of what someone is saying. 
Question 3 : I like to understand where other people are 'coming from', what experiences have led them to feel th... 
Question 4 : The most important part of my education has been learning to understand people who are very differen... 
Question 5 : I feel that the best way for me to achieve my own identity is to interact with a variety of other pe... 
Question 6 : I enjoy hearing the opinions of people who come from backgrounds / different to mine - it helps me to... 
Question 7 : I find that I can strengthen my own position through arguing with someone who disagrees with me. 
Question 8 : I am always interested in knowing why people say and believe the things they do. 
Question 9 : I often find myself arguing with the authors of books that I read, trying to logically figure out wh... 
Question 10 : It's important for me to remain as objective as possible when I analyze something. 
Question 11 : I try to think with people instead of against them. 
Question 12 : I have certain criteria I use in evaluating arguments. 
Question 13 : I'm more likely to try to understand someone else's opinion than to try to evaluate it. 
Question 14 : I try to point out weaknesses in other people's thinking to help them clarify their arguments. 
Question 15 : I tend to put myself in other people's shoes when discussing controversial issues, to see why they t... 
Question 16 : One could call my way of analysing things 'putting them on trial' because I am careful to consider a... 
Question 17 : I value the use of logic and reason over the incorporation of my own concerns when solving problems. 
Question 18 : I can obtain insight into opinions that differ from mine through empathy. 
Question 19 : When I encounter people whose opinions seem alien to me, I make a / deliberate effort to 'extend' myse... 
Question 20 : I spend time figuring out what's 'wrong' with things. For example, I'll / look for something in a lite... 

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Dataseries X:

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Histogram

Boxplots

4	2	3	4	3	4	3	5	2	4	3	3	4	2	3	4	2	4	2	3
4	3	4	2	4	4	4	4	1	3	3	3	4	3	2	3	4	3	NA	3
2	1	4	3	3	4	2	3	3	4	4	4	4	2	4	3	2	3	2	3
5	3	5	4	5	2	4	2	1	3	3	4	5	4	5	5	4	1	3	1
2	1	4	4	4	5	2	4	2	4	5	2	2	2	4	4	4	5	5	2
4	3	4	4	3	4	3	3	3	4	4	4	3	3	4	4	4	3	4	4
4	5	4	3	4	4	5	5	3	4	4	4	2	4	5	4	4	4	4	4
4	2	5	1	2	4	2	2	1	4	4	5	1	3	2	3	5	2	2	4
4	4	4	4	5	5	3	5	2	4	4	5	3	4	4	3	4	4	4	3
5	4	5	2	4	5	4	5	2	4	4	2	3	4	5	4	4	5	5	1
4	2	4	4	4	4	3	4	3	4	4	4	2	4	4	4	4	4	4	3
5	2	5	4	4	5	4	4	3	4	4	3	3	3	4	4	3	4	4	3
5	4	5	3	4	5	3	4	5	5	3	4	2	4	4	4	3	4	4	5
5	1	5	4	5	5	3	4	3	5	5	4	4	5	5	4	4	4	4	3
4	3	4	5	3	4	3	2	2	3	4	3	3	4	NA	3	3	2	4	2
5	2	5	3	4	4	4	4	2	4	4	3	4	3	4	4	5	3	4	3
4	4	5	2	3	4	1	4	1	4	4	4	1	3	4	5	4	4	4	3
4	2	1	1	3	3	5	4	1	2	5	4	4	4	3	2	4	4	4	3
4	4	4	2	4	4	4	4	2	4	4	4	4	4	2	2	2	3	4	4
5	4	5	1	4	5	4	5	1	5	3	4	2	4	5	4	4	5	5	4
4	4	3	3	4	4	5	4	3	4	2	3	3	3	3	3	3	3	4	3
4	3	4	3	4	3	4	4	1	4	4	3	4	4	4	3	4	3	4	3
4	2	3	2	3	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
4	1	5	2	4	5	1	5	4	4	4	5	4	4	3	3	2	4	2	2
4	4	4	4	5	5	4	4	3	4	4	4	4	4	4	4	4	4	4	4
5	4	5	4	4	5	4	5	2	4	4	3	4	4	5	2	2	5	4	4
5	2	2	2	5	4	4	5	3	4	2	5	4	5	4	2	5	4	2	4
5	1	5	3	4	4	4	5	3	5	5	4	5	3	5	3	3	4	4	3
4	2	4	2	4	4	3	4	1	5	5	3	4	3	3	2	4	4	4	3
4	3	4	2	2	4	3	4	3	4	4	3	4	3	4	3	4	4	4	3
5	1	5	4	4	5	2	4	2	4	5	3	4	4	4	3	1	4	4	2
4	1	4	4	3	5	4	5	3	4	3	4	3	3	4	3	5	4	4	3
5	3	4	3	3	4	4	4	3	3	3	3	4	3	4	3	4	3	3	2
5	2	3	3	4	5	3	4	1	4	5	3	3	2	4	3	3	4	4	2
4	3	4	2	3	5	3	4	1	3	4	3	4	1	3	2	3	3	3	1
4	1	5	3	5	4	3	5	1	4	4	4	4	4	3	3	4	3	4	4
4	5	5	3	4	5	3	4	3	3	3	3	4	4	4	3	3	4	2	2
3	2	4	2	3	3	3	4	3	3	3	3	2	4	3	3	3	4	3	3
4	2	3	1	4	2	2	1	2	4	3	4	4	2	2	3	4	4	1	4
4	2	3	2	4	3	4	3	1	3	4	2	4	4	3	3	3	4	3	2
5	3	4	4	4	5	3	4	3	4	5	4	5	3	4	3	3	4	4	2
4	2	4	1	4	5	3	3	1	4	4	1	4	2	3	2	3	4	1	1
2	1	3	1	3	4	3	4	1	4	4	3	4	2	3	3	3	3	3	2
4	2	3	3	2	2	2	3	2	5	5	4	3	3	3	4	4	3	3	5
4	4	4	4	4	4	4	4	4	4	4	4	4	4	4	4	3	4	4	2
4	2	2	2	1	4	4	4	4	5	4	4	4	3	5	3	4	4	5	4
4	1	5	4	2	4	4	5	2	4	4	4	2	4	5	4	2	4	4	2
5	1	2	3	4	5	4	2	2	4	3	5	4	4	4	3	4	2	4	2
4	2	5	4	4	5	4	5	4	4	4	4	4	4	5	4	5	5	4	4
5	1	3	3	4	4	2	4	3	5	4	4	3	1	4	3	4	3	3	3
2	5	2	2	5	5	5	4	1	5	5	5	4	5	2	4	4	5	4	4
5	3	5	5	4	3	2	5	2	4	4	4	4	3	4	3	4	3	2	4
4	1	5	2	4	4	4	3	3	4	3	NA	2	2	4	4	2	5	3	2
1	1	5	4	4	5	3	5	1	3	4	1	5	1	4	3	2	3	3	4
5	3	5	2	1	4	3	4	2	5	3	3	4	4	2	3	3	4	2	3
4	3	4	3	2	4	3	4	1	4	4	3	4	3	3	4	3	5	4	3
4	3	5	4	4	5	4	5	3	3	4	3	4	4	4	3	2	5	4	3
4	4	5	4	5	5	4	5	3	4	3	4	4	5	5	4	3	5	4	4
3	2	5	4	4	4	2	5	2	4	4	3	4	2	5	4	3	3	4	2
5	3	5	5	5	5	5	5	3	4	3	1	5	3	5	3	5	5	5	1
4	4	4	2	4	4	4	4	2	4	4	4	4	4	2	2	2	3	4	4
4	4	5	3	2	5	4	5	2	5	5	2	4	2	5	2	4	3	4	4
4	2	5	4	NA	4	2	5	1	4	4	2	4	1	2	2	4	4	3	2
5	3	4	1	5	4	4	3	2	5	4	3	2	5	5	5	4	4	1	NA
4	1	5	4	4	4	3	4	2	5	4	4	3	4	5	4	4	5	4	1
4	1	4	2	4	4	4	5	4	5	4	4	5	2	2	4	3	5	4	4
4	3	5	4	4	5	4	4	4	3	3	4	5	3	4	4	5	4	3	4
5	3	3	3	4	4	4	4	3	2	3	3	4	3	4	3	3	4	3	4
5	1	4	4	4	5	4	4	1	4	3	4	2	4	3	4	4	3	3	2
5	2	4	2	3	4	2	4	2	4	3	5	4	4	4	3	4	3	3	3
5	1	4	3	4	5	5	4	1	4	5	3	4	2	4	4	4	4	4	2
4	2	4	4	5	4	3	5	3	3	4	3	4	2	4	4	3	4	4	3
5	4	5	3	5	5	4	4	3	4	3	4	3	3	3	2	4	4	4	3
4	2	3	4	4	5	4	4	3	4	4	4	3	4	4	4	5	5	5	4
4	3	4	5	4	4	3	4	1	4	4	4	4	4	4	3	4	4	4	1
5	1	4	4	4	3	3	4	3	5	4	3	3	4	3	3	4	3	3	3
5	3	4	2	1	4	1	5	3	5	3	5	2	4	2	4	4	4	4	4
4	4	5	4	4	4	3	2	3	4	4	4	NA	3	3	2	4	4	4	4
5	4	3	2	4	4	3	4	3	3	4	2	4	4	4	4	4	3	3	3
5	2	4	3	4	4	4	5	2	4	5	4	3	3	5	4	3	5	4	2
4	1	5	2	3	4	2	4	1	2	4	3	4	4	4	2	3	3	4	2
2	2	2	3	4	5	4	4	3	4	3	4	3	3	4	3	3	3	4	2
5	5	5	4	2	5	4	5	5	5	5	4	4	3	5	5	2	2	3	5
4	3	4	1	5	5	5	5	4	2	4	4	2	5	5	3	4	5	3	4
5	5	4	3	4	4	4	4	5	5	3	4	4	4	5	4	3	4	4	4
4	4	5	2	4	4	3	4	2	5	5	4	4	4	4	4	4	4	3	3
4	2	3	2	4	5	3	5	3	5	3	2	5	2	2	3	5	2	4	2
4	3	5	4	5	4	5	5	1	4	3	5	4	2	4	4	4	5	5	2
4	2	5	5	5	5	2	4	2	5	5	3	4	4	5	2	3	5	5	2
5	2	5	5	5	5	3	4	4	5	4	3	4	4	5	5	4	5	5	3
2	2	4	2	5	4	2	4	2	5	5	3	5	3	4	3	4	5	4	5
5	1	5	4	4	5	3	4	2	4	4	3	3	3	4	3	3	3	3	2
5	5	4	1	1	3	5	5	1	4	1	5	5	5	1	5	5	3	4	5
5	4	5	5	5	5	3	5	2	5	2	4	3	4	4	4	5	5	5	4
4	5	4	2	4	4	4	5	2	1	3	4	4	4	1	2	3	4	2	4
4	4	5	2	4	1	4	4	2	4	3	4	2	4	5	4	3	3	4	2
4	5	4	1	5	5	4	5	2	2	2	1	5	4	1	2	4	1	2	1
4	4	5	3	4	4	4	5	4	3	4	2	3	1	4	2	3	2	3	4
4	2	4	3	5	4	4	4	3	3	4	4	2	4	4	3	4	4	4	3
4	4	5	4	4	5	5	4	4	5	5	4	3	4	4	4	5	5	3	4
4	2	4	2	4	5	4	4	1	5	1	2	4	4	1	5	5	1	2	4
4	4	2	2	2	4	4	4	4	4	3	2	4	2	4	3	3	4	4	2
5	2	5	4	5	5	4	5	2	3	4	5	5	4	1	4	2	2	5	1
3	3	5	2	4	5	4	3	3	2	3	4	3	3	3	2	4	4	4	5
5	3	4	4	4	5	4	4	2	4	2	4	4	4	4	3	4	4	3	3
2	3	4	3	4	5	4	4	3	4	3	4	4	2	4	3	3	4	3	4
4	3	4	2	5	5	5	5	3	4	4	4	4	4	4	5	5	2	4	4
5	2	5	4	3	4	3	5	2	4	4	2	4	3	5	3	3	4	4	2
4	3	4	3	4	4	3	4	2	4	3	4	4	3	4	3	4	4	3	4
5	3	5	5	4	5	5	5	4	4	3	2	3	2	4	4	5	5	4	3
4	2	5	3	5	5	5	4	2	4	4	3	5	3	5	3	4	5	4	3
4	3	5	5	3	4	4	4	2	5	3	3	2	4	2	3	5	2	4	5
4	2	5	3	4	5	3	4	2	5	4	4	4	5	4	4	3	4	2	3
4	1	5	4	5	4	4	5	1	5	5	3	4	3	5	3	4	5	5	3
5	4	5	4	5	5	5	5	4	4	4	3	4	2	5	2	2	4	4	2
4	2	5	4	5	5	4	4	2	2	4	4	4	2	4	2	4	4	4	5
1	2	4	1	4	4	4	2	1	4	4	3	5	2	2	1	4	4	1	1
4	2	4	3	2	4	3	4	3	4	3	4	2	4	4	3	4	4	3	4
3	4	5	4	3	4	2	5	3	2	4	4	2	3	2	NA	NA	NA	NA	NA
4	4	5	4	5	5	4	5	4	2	5	4	4	2	4	3	3	4	4	4
4	4	2	1	5	4	4	4	1	4	4	4	2	4	4	2	4	5	2	1
4	1	4	4	3	2	4	2	4	5	4	4	2	4	2	2	4	3	3	3
4	4	3	3	3	3	3	3	3	4	4	3	3	3	3	3	3	3	3	3
4	3	5	3	4	5	2	4	4	4	5	3	3	5	5	3	1	5	4	4
4	5	4	3	4	3	4	4	2	4	3	4	4	2	5	4	3	4	3	2
4	3	5	3	4	4	4	4	1	3	3	1	4	2	3	3	4	3	3	4
4	2	3	2	5	3	4	4	2	4	4	3	5	5	4	3	3	2	3	2
5	2	5	2	5	4	4	5	3	4	4	5	2	4	4	4	4	4	4	2
5	2	4	3	5	4	4	4	3	4	5	5	4	3	4	4	4	3	3	3
5	1	4	4	4	5	5	4	3	4	4	3	3	3	4	3	3	3	3	4
3	2	5	3	4	5	4	4	3	5	4	3	2	3	4	4	4	4	4	3
4	4	3	2	3	4	2	2	3	3	2	4	3	3	4	2	4	2	2	1
5	4	5	4	5	4	5	5	4	2	4	4	3	3	2	3	5	5	2	3
4	2	5	3	4	4	2	4	2	4	4	4	2	3	2	4	4	4	4	4
5	4	5	3	5	4	4	2	3	4	4	4	3	5	3	4	4	4	4	4
5	1	3	4	4	4	4	4	3	4	4	4	3	4	3	3	4	4	3	3
4	2	2	3	4	4	4	4	2	3	3	4	3	2	5	3	3	4	4	3
5	4	4	4	3	4	5	4	1	3	4	4	4	5	3	4	3	3	4	2
5	4	5	4	4	4	4	5	3	4	3	4	2	4	4	3	5	4	4	3
5	4	5	4	4	5	3	4	2	4	3	4	3	4	2	4	3	3	2	4
4	2	4	3	3	4	4	5	2	4	4	4	4	3	4	4	4	4	4	4
5	2	4	5	5	5	4	4	1	4	4	4	5	5	5	3	4	3	3	4
5	1	4	3	4	4	3	4	2	4	4	4	3	3	4	4	3	3	4	3
4	3	2	2	2	2	4	4	2	3	3	3	3	3	3	2	3	4	4	3
4	3	4	1	2	3	2	4	2	5	2	4	2	4	4	4	4	3	4	4
5	2	3	3	4	4	4	4	3	4	4	5	2	4	4	4	4	3	4	4
3	3	3	2	4	5	4	2	3	2	4	4	4	4	4	3	3	4	3	4
4	1	3	4	4	3	4	4	3	4	3	4	3	4	3	2	3	3	4	2
5	1	4	3	4	3	3	4	1	5	4	4	3	3	3	3	3	3	3	3
5	2	5	2	5	4	4	4	2	4	2	4	4	5	2	4	4	4	2	4
5	1	5	4	5	5	3	5	2	5	5	3	5	2	5	3	5	5	5	1
4	3	5	4	5	5	3	4	2	4	3	4	3	NA	4	3	3	3	4	4
5	2	4	4	4	5	5	5	3	5	3	4	2	4	5	4	4	4	5	4
5	2	5	5	5	5	5	5	5	5	5	4	5	4	5	5	5	5	5	5
5	2	4	4	5	4	4	4	2	4	5	4	3	3	4	2	3	3	4	2
4	1	5	3	4	4	4	5	4	4	4	3	3	4	4	4	3	4	4	3
4	4	4	4	4	4	4	4	4	4	4	4	4	4	4	4	4	4	4	4
4	4	5	1	2	5	2	5	5	4	2	5	5	5	4	5	4	1	1	5
5	1	4	3	2	4	3	2	1	4	4	4	4	4	2	3	4	4	2	3
5	4	4	1	4	5	4	4	1	5	5	4	5	4	4	4	4	4	4	4
4	2	4	3	5	4	5	4	2	4	4	4	4	4	4	3	5	4	4	3
2	3	4	3	4	3	3	4	2	5	5	1	5	1	3	1	5	3	3	1
5	3	3	2	4	2	5	4	1	2	3	4	4	2	1	4	3	1	2	2
2	4	3	4	2	4	4	5	4	4	4	3	2	4	3	4	NA	3	3	4
5	3	4	3	3	4	5	4	2	4	4	4	3	4	3	3	3	3	3	NA
5	4	4	2	4	5	3	5	2	5	3	4	5	5	2	3	5	5	2	5
5	2	4	3	4	4	3	4	2	4	4	3	5	3	4	3	4	4	4	3
4	2	4	4	4	4	2	3	2	4	4	4	4	4	4	4	4	4	4	4
2	5	5	4	5	5	5	2	2	2	4	3	4	4	4	4	4	4	4	3
5	2	4	4	5	5	4	5	3	5	3	3	4	4	4	3	4	3	4	3
4	1	3	3	3	4	4	3	2	4	4	3	4	3	3	3	3	4	3	3
4	2	4	3	4	4	3	2	3	3	4	3	4	3	4	3	3	3	4	3
5	2	4	3	5	4	4	4	2	3	2	4	5	4	4	3	4	2	4	1
4	2	4	4	4	2	2	4	2	4	4	4	4	4	4	4	5	4	4	4
5	3	4	4	4	4	4	4	4	4	4	2	3	5	4	3	4	4	3	4
4	2	4	2	4	4	4	3	1	4	3	2	3	2	3	2	3	4	3	2
3	1	3	2	3	3	4	4	2	5	4	5	4	4	2	3	2	4	3	2
4	3	4	4	5	4	4	3	2	4	4	4	3	3	4	3	4	4	4	5
4	4	3	4	5	5	5	5	4	3	3	2	4	4	2	2	4	3	3	4
3	4	4	3	4	3	5	4	3	4	2	4	2	3	3	3	3	4	3	4
5	4	5	5	5	5	4	5	4	5	5	5	5	5	5	5	5	2	4	5
2	4	5	2	4	5	5	5	1	4	2	5	5	4	4	4	2	3	3	1
4	4	3	1	4	4	2	4	3	2	4	2	4	4	3	2	3	4	5	3
5	3	5	4	4	5	4	5	1	5	5	4	5	4	5	4	5	5	5	5
5	4	5	3	5	5	5	4	3	5	4	5	5	4	3	4	2	3	3	3
5	2	5	3	4	4	4	4	4	5	5	4	4	3	4	4	4	4	3	3
4	3	4	3	4	5	4	4	2	4	3	2	4	3	3	3	4	3	4	3
5	1	1	4	5	4	3	4	2	4	4	3	4	3	4	4	3	4	2	2
5	3	4	3	4	3	3	4	2	4	4	3	4	3	4	4	4	3	3	2
4	2	4	4	5	5	4	4	4	4	4	3	3	4	3	3	3	4	3	4
4	3	5	4	4	4	3	4	3	4	4	3	4	3	4	3	4	4	4	4
2	2	5	4	4	5	3	5	2	4	3	3	4	3	5	4	4	4	4	3
4	3	5	3	3	4	3	5	2	4	5	3	5	3	5	5	3	5	5	2
2	4	4	4	3	5	5	4	1	3	3	2	4	3	2	4	2	2	2	3
5	2	3	1	3	4	3	4	1	4	4	3	3	3	3	2	4	4	4	1
5	2	4	3	4	4	4	4	3	4	4	3	4	2	5	3	4	4	5	4
4	3	5	5	5	5	4	4	4	4	2	4	2	3	4	3	3	3	4	2
4	2	5	3	4	4	3	2	2	4	4	3	4	4	4	3	3	5	4	2
4	1	5	5	5	5	4	5	1	4	4	2	4	1	4	3	4	3	4	1
4	2	5	4	5	4	4	4	2	4	4	2	4	3	4	2	3	4	4	4
4	5	5	2	4	5	5	4	1	5	2	2	4	5	4	5	1	4	4	1
4	4	4	2	1	4	3	2	1	4	4	4	3	2	4	4	3	3	1	1
4	3	4	2	4	4	3	4	3	4	4	4	4	3	2	3	3	2	2	2
4	1	5	4	5	5	1	4	3	5	4	3	4	2	5	3	4	4	5	5
4	1	4	1	3	4	1	3	1	4	3	4	4	4	3	2	2	3	3	4
4	3	3	3	3	3	3	NA	3	3	3	3	3	3	3	3	3	3	3	3
5	2	4	3	5	4	3	4	3	5	4	5	5	4	3	4	3	3	4	4
4	1	4	2	5	4	2	4	1	2	3	3	4	3	2	2	3	4	3	3
4	1	4	3	5	5	3	5	1	4	4	4	3	4	4	5	4	5	4	3
5	4	5	3	4	4	4	3	2	4	5	4	4	4	5	5	4	4	3	3
5	4	5	4	2	5	3	4	2	5	3	4	4	3	5	4	4	4	4	3
4	5	5	3	5	5	5	4	3	5	3	4	3	4	4	4	4	4	3	4
5	1	3	3	4	4	3	4	2	4	3	4	3	3	4	3	3	3	4	3
4	4	4	2	3	4	4	3	4	3	4	2	4	4	3	3	3	4	4	3
5	5	5	4	4	3	5	4	3	4	2	4	2	5	4	2	4	4	4	5
1	1	5	1	5	5	1	5	1	5	5	5	4	3	5	5	3	3	3	3
4	3	3	3	5	4	4	5	2	3	5	5	4	5	4	5	4	3	4	2
3	2	5	2	5	5	5	5	3	5	5	4	2	4	5	5	4	5	5	3
4	4	4	3	4	4	4	4	4	4	4	4	4	4	4	3	4	4	3	4
5	3	4	2	2	5	4	5	2	4	4	4	5	5	5	4	3	3	4	3
4	4	5	4	5	5	2	3	1	4	3	4	3	2	3	3	2	4	4	4
5	1	4	3	4	5	4	4	3	4	5	3	4	4	4	4	5	4	4	3
5	2	3	3	4	4	3	5	3	5	5	3	4	3	4	2	3	4	4	5
4	4	4	2	4	4	3	4	3	4	4	4	2	4	4	3	4	4	4	3
4	2	3	4	4	4	2	1	3	3	2	2	4	3	4	3	3	3	2	2
3	3	4	2	4	2	4	4	2	4	3	4	3	4	4	3	4	4	3	4
4	2	3	4	3	3	4	5	3	4	4	4	2	4	4	4	4	3	4	2
2	4	5	4	4	4	5	5	4	5	4	4	2	4	4	2	2	3	4	3
5	2	5	4	5	5	5	4	2	4	4	4	4	3	4	4	5	3	4	3
4	3	4	2	5	5	4	5	1	2	4	3	4	3	5	3	2	3	4	1
5	3	4	1	2	3	4	4	3	4	4	4	4	4	4	4	4	4	4	3
4	4	3	4	4	4	4	4	4	4	3	4	4	4	5	4	4	3	4	4
2	4	3	3	4	4	4	3	3	4	2	4	3	4	2	3	4	3	3	3
4	5	5	3	2	3	3	5	4	5	3	3	2	4	3	3	5	3	3	4
2	2	5	5	5	5	5	5	3	4	5	4	4	4	5	4	5	5	5	5
3	1	4	2	3	5	4	4	3	5	4	5	4	4	4	3	4	3	4	3
3	4	4	2	3	2	3	2	3	4	2	4	2	3	2	3	2	2	2	2
3	3	2	4	4	2	3	2	4	2	4	4	2	3	2	3	4	NA	2	4
5	1	4	4	4	3	1	4	2	5	3	4	4	3	4	3	4	3	4	3
5	2	4	4	4	4	4	4	4	5	4	4	4	5	4	3	4	4	3	4
3	2	4	3	5	4	NA	4	3	4	4	4	5	3	4	2	3	4	4	4
5	4	2	2	4	5	4	4	2	5	4	5	4	4	4	4	4	3	4	2
5	2	4	3	5	4	3	4	2	5	3	4	4	4	5	3	4	3	4	4
4	3	3	3	4	4	3	3	4	5	5	3	3	3	3	3	3	3	3	3
4	4	4	4	4	4	4	4	4	5	5	4	3	2	4	4	4	4	3	3
4	5	NA	3	4	4	4	5	1	4	4	2	2	4	2	2	4	2	2	4
4	4	5	3	5	5	4	3	2	3	4	4	4	3	4	3	3	5	3	5
5	3	4	3	4	5	5	5	2	4	3	2	4	2	4	2	2	3	4	2
4	4	5	4	4	5	4	4	4	4	4	4	4	4	4	3	3	4	3	4
5	2	4	3	1	3	4	1	4	5	3	4	1	4	4	5	2	3	NA	2
5	1	4	4	4	5	5	5	3	4	4	4	5	4	4	4	3	4	4	4
4	3	4	4	4	5	4	4	2	4	4	2	4	4	4	3	5	3	2	3
3	3	4	4	3	4	3	4	4	3	4	4	3	4	2	3	3	3	4	3
4	4	4	3	4	4	2	3	2	4	4	2	5	2	4	3	3	3	4	2
4	4	5	3	4	5	4	4	1	4	3	3	4	2	2	3	5	2	3	3
3	1	4	1	3	2	2	4	1	3	4	4	4	2	5	3	3	3	4	1
4	2	5	3	4	3	5	5	3	5	3	4	3	4	5	3	4	2	4	5
5	3	4	5	5	5	4	4	3	4	4	5	3	4	4	5	5	2	3	4
4	1	5	5	5	5	5	5	4	5	5	3	5	1	5	5	5	5	5	3
2	4	3	3	4	4	4	5	2	4	3	4	3	4	4	4	4	4	3	3
4	2	3	4	5	5	3	4	2	5	5	4	3	4	3	3	4	3	3	3
5	3	3	2	4	3	3	4	2	5	3	4	4	3	3	3	3	3	3	3
5	2	2	3	NA	NA	NA	3	3	3	3	3	NA	3	3	3	3	3	4	4
5	4	5	3	3	4	4	5	3	5	4	3	5	4	5	3	4	3	3	1
4	3	4	3	3	3	3	4	3	3	4	3	3	4	3	3	3	3	4	3
5	3	5	4	5	5	1	5	4	5	5	3	4	3	5	4	3	2	4	3
5	2	3	1	2	3	2	2	5	5	3	2	4	3	3	3	3	4	3	3
5	1	3	2	4	3	3	4	3	2	3	3	4	3	3	3	3	3	4	3
5	3	4	4	4	5	4	4	4	3	4	4	3	4	4	4	4	3	4	4
5	5	5	5	5	5	4	5	5	5	4	5	5	5	5	5	4	3	5	5
4	2	5	4	5	3	3	4	5	4	4	4	4	4	3	5	4	3	5	3
5	4	2	3	3	3	2	2	2	3	3	4	4	3	3	4	2	2	4	2
4	1	5	3	5	5	4	4	3	5	5	4	4	3	4	3	4	5	4	3
5	2	4	4	3	4	3	4	2	4	5	4	3	3	4	4	3	3	4	3
4	1	4	3	4	4	4	4	3	4	4	3	4	4	4	3	4	5	4	2
4	2	5	3	4	4	3	3	2	4	4	4	4	3	4	3	3	4	2	2
4	3	2	2	2	3	2	2	1	3	2	1	1	3	2	4	2	4	2	1
4	5	5	5	5	5	5	5	3	5	2	5	5	5	4	4	5	4	4	4
3	3	3	2	2	3	2	2	2	2	3	4	4	2	3	2	2	2	3	3
3	2	2	2	4	4	4	3	2	4	3	1	2	3	2	4	4	4	2	3
4	3	4	4	4	4	3	3	1	4	3	2	3	4	2	3	4	4	4	2
4	3	4	4	5	5	4	4	4	4	3	4	3	3	3	4	4	4	4	4
5	3	1	2	4	3	4	3	3	4	4	4	3	3	4	4	4	4	3	4
3	2	2	4	4	4	3	4	1	5	4	4	4	3	3	3	4	4	2	4
3	3	4	4	3	4	4	4	2	4	4	2	3	4	2	4	2	3	4	3
5	3	4	4	4	4	3	4	2	4	3	4	4	4	4	4	4	4	4	2
4	4	5	3	4	5	5	4	2	4	3	4	4	4	4	4	5	4	3	3
5	NA	5	5	5	5	5	5	5	5	5	5	5	5	5	5	5	5	5	1
2	4	4	3	5	4	4	4	1	4	3	5	4	4	4	3	5	4	5	3
4	3	4	4	5	4	3	5	2	5	5	4	5	4	5	4	4	4	4	4
4	4	5	5	5	5	5	4	4	5	5	4	5	5	5	5	5	5	5	5
3	2	5	4	4	5	1	5	1	3	5	4	5	3	4	3	5	3	5	2
5	3	4	4	4	4	4	5	3	4	3	4	3	4	4	4	4	4	4	3
2	4	4	3	5	4	5	4	1	3	3	3	5	5	4	3	4	4	3	2
5	3	4	4	5	4	4	4	2	3	3	3	3	3	4	3	3	3	3	3
5	3	4	3	4	4	3	4	1	5	4	3	4	1	3	3	4	4	4	2
4	1	3	4	4	4	3	5	2	4	4	4	4	4	4	3	3	4	4	4
4	2	2	3	4	3	2	4	2	4	3	3	4	3	4	4	4	4	3	5
5	4	5	4	4	5	5	5	3	4	3	3	3	4	4	3	4	5	4	3
3	5	4	4	2	2	5	4	3	5	1	1	1	3	4	4	2	1	1	3
3	2	5	4	5	4	5	4	1	3	4	1	4	2	4	3	4	5	4	1
5	5	4	4	5	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
5	2	5	4	5	5	2	5	1	3	4	4	4	2	5	3	2	4	4	4
5	1	5	3	4	4	4	4	1	3	5	4	5	4	4	2	3	5	2	1
5	1	5	4	4	5	5	5	4	5	NA	4	4	4	5	5	5	4	4	4
3	2	2	4	5	3	3	5	2	2	2	4	2	3	4	1	4	4	2	2
4	3	NA	5	4	4	NA	5	4	5	3	5	5	4	3	5	4	4	4	5
5	3	4	4	3	4	4	5	3	3	4	3	4	3	4	4	3	4	4	3
4	1	5	3	5	5	4	4	3	4	5	3	4	4	5	4	4	5	4	3
4	2	4	3	4	3	4	4	3	3	3	2	4	4	1	3	3	2	4	4
2	4	2	4	1	1	1	2	5	4	2	3	1	1	4	2	2	2	NA	1
4	3	4	4	4	4	3	4	3	3	5	4	4	3	3	4	3	4	3	4
5	3	3	4	2	2	5	4	4	3	2	2	3	4	5	2	3	3	1	3
4	2	4	4	4	4	4	3	4	4	4	5	2	5	5	4	2	4	4	4
5	3	4	2	5	5	4	5	2	5	5	3	5	5	5	3	4	4	4	2
5	1	5	4	4	5	5	5	4	5	5	4	4	4	5	4	5	5	4	4
3	3	2	4	3	3	2	4	3	2	5	3	5	2	3	NA	2	3	2	1
4	3	2	3	3	2	3	3	4	3	4	3	4	3	3	3	4	3	3	4
3	3	4	4	4	4	3	4	3	4	4	4	4	4	3	4	4	4	2	4
5	2	4	4	4	4	5	4	2	4	4	4	4	2	4	4	4	4	4	3
4	4	3	5	4	4	5	5	4	5	3	2	1	4	4	5	5	2	4	2
5	4	3	4	4	5	4	4	3	5	4	2	3	4	2	2	3	3	3	3
4	3	2	2	3	2	4	3	4	4	4	3	2	2	2	4	5	2	3	4
4	3	4	3	4	5	3	5	1	4	5	1	4	3	3	3	2	4	4	3
5	4	5	4	5	5	5	5	2	4	3	4	4	4	5	4	5	5	5	5
4	4	5	4	1	3	3	5	2	4	5	5	5	4	2	3	3	4	4	4
5	4	5	3	4	5	5	4	2	5	4	4	4	4	5	4	4	3	4	3
3	1	4	4	5	4	2	3	1	4	4	4	3	4	5	3	3	4	3	2
4	2	4	4	5	5	4	5	2	3	4	4	4	3	4	3	3	4	4	3
3	3	4	4	4	4	3	4	2	3	4	2	4	3	4	2	4	3	4	3
5	3	4	2	4	5	5	4	3	5	5	3	4	3	4	3	4	4	3	2
5	4	4	4	2	5	5	4	4	4	4	4	2	4	4	4	1	3	5	4
3	3	3	3	3	3	3	3	3	3	3	3	3	3	3	3	3	3	3	3
5	4	5	3	5	4	5	4	3	5	5	3	5	3	4	3	3	4	4	4

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	9 seconds
R Server	'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 9 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=74593&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]9 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=74593&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=74593&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	9 seconds
R Server	'RServer@AstonUniversity' @ vre.aston.ac.uk

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	1.14	407	26	0.88	282	23	0.85
2	-0.27	116	206	-0.28	97	150	-0.21
3	1.07	382	28	0.86	260	25	0.82
4	0.18	169	108	0.22	146	86	0.26
5	0.92	346	40	0.79	254	32	0.78
6	1.15	399	19	0.91	274	17	0.88
7	0.59	251	56	0.64	194	46	0.62
8	1.05	375	28	0.86	275	25	0.83
9	-0.49	72	235	-0.53	62	171	-0.47
10	0.98	347	23	0.88	259	22	0.84
11	0.74	274	29	0.81	215	26	0.78
12	0.51	227	57	0.6	195	46	0.62
13	0.6	256	57	0.64	207	50	0.61
14	0.42	203	63	0.53	173	53	0.53
15	0.72	290	53	0.69	222	46	0.66
16	0.35	168	51	0.53	140	48	0.49
17	0.58	234	42	0.7	189	38	0.67
18	0.62	244	39	0.72	195	33	0.71
19	0.54	228	52	0.63	197	44	0.63
20	0.08	148	123	0.09	123	94	0.13

\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 & 1.14 & 407 & 26 & 0.88 & 282 & 23 & 0.85 \tabularnewline
2 & -0.27 & 116 & 206 & -0.28 & 97 & 150 & -0.21 \tabularnewline
3 & 1.07 & 382 & 28 & 0.86 & 260 & 25 & 0.82 \tabularnewline
4 & 0.18 & 169 & 108 & 0.22 & 146 & 86 & 0.26 \tabularnewline
5 & 0.92 & 346 & 40 & 0.79 & 254 & 32 & 0.78 \tabularnewline
6 & 1.15 & 399 & 19 & 0.91 & 274 & 17 & 0.88 \tabularnewline
7 & 0.59 & 251 & 56 & 0.64 & 194 & 46 & 0.62 \tabularnewline
8 & 1.05 & 375 & 28 & 0.86 & 275 & 25 & 0.83 \tabularnewline
9 & -0.49 & 72 & 235 & -0.53 & 62 & 171 & -0.47 \tabularnewline
10 & 0.98 & 347 & 23 & 0.88 & 259 & 22 & 0.84 \tabularnewline
11 & 0.74 & 274 & 29 & 0.81 & 215 & 26 & 0.78 \tabularnewline
12 & 0.51 & 227 & 57 & 0.6 & 195 & 46 & 0.62 \tabularnewline
13 & 0.6 & 256 & 57 & 0.64 & 207 & 50 & 0.61 \tabularnewline
14 & 0.42 & 203 & 63 & 0.53 & 173 & 53 & 0.53 \tabularnewline
15 & 0.72 & 290 & 53 & 0.69 & 222 & 46 & 0.66 \tabularnewline
16 & 0.35 & 168 & 51 & 0.53 & 140 & 48 & 0.49 \tabularnewline
17 & 0.58 & 234 & 42 & 0.7 & 189 & 38 & 0.67 \tabularnewline
18 & 0.62 & 244 & 39 & 0.72 & 195 & 33 & 0.71 \tabularnewline
19 & 0.54 & 228 & 52 & 0.63 & 197 & 44 & 0.63 \tabularnewline
20 & 0.08 & 148 & 123 & 0.09 & 123 & 94 & 0.13 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=74593&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]1.14[/C][C]407[/C][C]26[/C][C]0.88[/C][C]282[/C][C]23[/C][C]0.85[/C][/ROW]
[ROW][C]2[/C][C]-0.27[/C][C]116[/C][C]206[/C][C]-0.28[/C][C]97[/C][C]150[/C][C]-0.21[/C][/ROW]
[ROW][C]3[/C][C]1.07[/C][C]382[/C][C]28[/C][C]0.86[/C][C]260[/C][C]25[/C][C]0.82[/C][/ROW]
[ROW][C]4[/C][C]0.18[/C][C]169[/C][C]108[/C][C]0.22[/C][C]146[/C][C]86[/C][C]0.26[/C][/ROW]
[ROW][C]5[/C][C]0.92[/C][C]346[/C][C]40[/C][C]0.79[/C][C]254[/C][C]32[/C][C]0.78[/C][/ROW]
[ROW][C]6[/C][C]1.15[/C][C]399[/C][C]19[/C][C]0.91[/C][C]274[/C][C]17[/C][C]0.88[/C][/ROW]
[ROW][C]7[/C][C]0.59[/C][C]251[/C][C]56[/C][C]0.64[/C][C]194[/C][C]46[/C][C]0.62[/C][/ROW]
[ROW][C]8[/C][C]1.05[/C][C]375[/C][C]28[/C][C]0.86[/C][C]275[/C][C]25[/C][C]0.83[/C][/ROW]
[ROW][C]9[/C][C]-0.49[/C][C]72[/C][C]235[/C][C]-0.53[/C][C]62[/C][C]171[/C][C]-0.47[/C][/ROW]
[ROW][C]10[/C][C]0.98[/C][C]347[/C][C]23[/C][C]0.88[/C][C]259[/C][C]22[/C][C]0.84[/C][/ROW]
[ROW][C]11[/C][C]0.74[/C][C]274[/C][C]29[/C][C]0.81[/C][C]215[/C][C]26[/C][C]0.78[/C][/ROW]
[ROW][C]12[/C][C]0.51[/C][C]227[/C][C]57[/C][C]0.6[/C][C]195[/C][C]46[/C][C]0.62[/C][/ROW]
[ROW][C]13[/C][C]0.6[/C][C]256[/C][C]57[/C][C]0.64[/C][C]207[/C][C]50[/C][C]0.61[/C][/ROW]
[ROW][C]14[/C][C]0.42[/C][C]203[/C][C]63[/C][C]0.53[/C][C]173[/C][C]53[/C][C]0.53[/C][/ROW]
[ROW][C]15[/C][C]0.72[/C][C]290[/C][C]53[/C][C]0.69[/C][C]222[/C][C]46[/C][C]0.66[/C][/ROW]
[ROW][C]16[/C][C]0.35[/C][C]168[/C][C]51[/C][C]0.53[/C][C]140[/C][C]48[/C][C]0.49[/C][/ROW]
[ROW][C]17[/C][C]0.58[/C][C]234[/C][C]42[/C][C]0.7[/C][C]189[/C][C]38[/C][C]0.67[/C][/ROW]
[ROW][C]18[/C][C]0.62[/C][C]244[/C][C]39[/C][C]0.72[/C][C]195[/C][C]33[/C][C]0.71[/C][/ROW]
[ROW][C]19[/C][C]0.54[/C][C]228[/C][C]52[/C][C]0.63[/C][C]197[/C][C]44[/C][C]0.63[/C][/ROW]
[ROW][C]20[/C][C]0.08[/C][C]148[/C][C]123[/C][C]0.09[/C][C]123[/C][C]94[/C][C]0.13[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=74593&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=74593&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	1.14	407	26	0.88	282	23	0.85
2	-0.27	116	206	-0.28	97	150	-0.21
3	1.07	382	28	0.86	260	25	0.82
4	0.18	169	108	0.22	146	86	0.26
5	0.92	346	40	0.79	254	32	0.78
6	1.15	399	19	0.91	274	17	0.88
7	0.59	251	56	0.64	194	46	0.62
8	1.05	375	28	0.86	275	25	0.83
9	-0.49	72	235	-0.53	62	171	-0.47
10	0.98	347	23	0.88	259	22	0.84
11	0.74	274	29	0.81	215	26	0.78
12	0.51	227	57	0.6	195	46	0.62
13	0.6	256	57	0.64	207	50	0.61
14	0.42	203	63	0.53	173	53	0.53
15	0.72	290	53	0.69	222	46	0.66
16	0.35	168	51	0.53	140	48	0.49
17	0.58	234	42	0.7	189	38	0.67
18	0.62	244	39	0.72	195	33	0.71
19	0.54	228	52	0.63	197	44	0.63
20	0.08	148	123	0.09	123	94	0.13

Pearson correlations of survey scores (and p-values)
	mean	(Ps-Ns)/(Ps+Ns)	(Pc-Nc)/(Pc+Nc)
mean	1 (0)	0.959 (0)	0.959 (0)
(Ps-Ns)/(Ps+Ns)	0.959 (0)	1 (0)	0.999 (0)
(Pc-Nc)/(Pc+Nc)	0.959 (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) & 0.959 (0) & 0.959 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.959 (0) & 1 (0) & 0.999 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.959 (0) & 0.999 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=74593&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]0.959 (0)[/C][C]0.959 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.959 (0)[/C][C]1 (0)[/C][C]0.999 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.959 (0)[/C][C]0.999 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=74593&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=74593&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)	0.959 (0)	0.959 (0)
(Ps-Ns)/(Ps+Ns)	0.959 (0)	1 (0)	0.999 (0)
(Pc-Nc)/(Pc+Nc)	0.959 (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)	0.915 (0)	0.878 (0)
(Ps-Ns)/(Ps+Ns)	0.915 (0)	1 (0)	0.952 (0)
(Pc-Nc)/(Pc+Nc)	0.878 (0)	0.952 (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) & 0.915 (0) & 0.878 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.915 (0) & 1 (0) & 0.952 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.878 (0) & 0.952 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=74593&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]0.915 (0)[/C][C]0.878 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.915 (0)[/C][C]1 (0)[/C][C]0.952 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.878 (0)[/C][C]0.952 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=74593&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=74593&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)	0.915 (0)	0.878 (0)
(Ps-Ns)/(Ps+Ns)	0.915 (0)	1 (0)	0.952 (0)
(Pc-Nc)/(Pc+Nc)	0.878 (0)	0.952 (0)	1 (0)

Parameters (Session):

par1 = 1 2 3 4 5 ;

Parameters (R input):

par1 = 1 2 3 4 5 ;

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

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