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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

Sun, 03 Oct 2010 16:55:42 +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/Oct/03/t1286125834b31k3l1ml6js8dp.htm/, Retrieved Fri, 03 May 2024 14:23:09 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=80353, Retrieved Fri, 03 May 2024 14:23:09 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

561

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] [b98453cac15ba1066b407e146608df68]
F    D      [Survey Scores] [ATTLES Scores] [2010-10-03 16:55:42] [d76b387543b13b5e3afd8ff9e5fdc89f] [Current]
-             [Survey Scores] [Task 5 (b)] [2010-10-12 14:47:16] [247f085ab5b7724f755ad01dc754a3e8] 
- RMPD        [Exercise 1.13] [Workshop 2 - Task 1] [2011-10-06 15:56:44] [c53df38315e3cbde2dbe0de809195ef2] 
- RMPD        [Exercise 1.13] [Workshop 2 - Task 1] [2011-10-06 15:56:44] [c53df38315e3cbde2dbe0de809195ef2] 
- RMPD        [Exercise 1.13] [Workshop 2 - Task 1] [2011-10-06 15:56:44] [c53df38315e3cbde2dbe0de809195ef2] 
- RMPD        [Exercise 1.13] [Workshop 2 - Task 1] [2011-10-06 15:56:44] [c53df38315e3cbde2dbe0de809195ef2] 
- RMPD        [Exercise 1.13] [Workshop 2 - Task 1] [2011-10-06 15:56:44] [c53df38315e3cbde2dbe0de809195ef2] 
- RMPD        [Exercise 1.13] [Workshop 2 - Task 3] [2011-10-06 16:14:04] [c53df38315e3cbde2dbe0de809195ef2] 
- R           [Survey Scores] [Workshop 2 - Task 5] [2011-10-06 16:46:07] [fbaf17a8836493f6de0f4e0e997711e1] 
- RM          [Survey Scores] [] [2011-10-06 20:55:02] [ee8c3a74bf3b349877806e9a50913c60] 
- RM          [Survey Scores] [Week 2 Opdracht 5b] [2011-10-09 08:49:22] [d2d464c5b110c95dc0c66eb9ae81f8ec] 
- R           [Survey Scores] [taak 5] [2011-10-10 07:47:04] [c4580079d5d2b3f0ba412f27cdc441be] 
- RM          [Survey Scores] [opdracht 5-2] [2011-10-10 18:54:55] [8fcdd1f5b88bf5ac5d2a0b8a91219b89] 
- RM          [Survey Scores] [] [2011-10-11 08:16:15] [ad2d4c5ace9fa07b356a7b5098237581] 
- R           [Survey Scores] [] [2011-10-11 09:46:12] [18e0b15711387f6270134133fa101957] 
- RMPD        [Exercise 1.13] [Task 2] [2011-10-11 14:26:01] [0f81819b439c6e991d1a2004e9982756] 
- RMPD        [Exercise 1.13] [Task 3] [2011-10-11 14:26:37] [0f81819b439c6e991d1a2004e9982756] 
- RMP         [Kendall tau Correlation Matrix] [test] [2011-10-11 14:47:26] [25b6caf3839c2bdc14961e5bff2d6373] 
- R           [Survey Scores] [Workshop 2 Task 5.2] [2011-10-11 15:07:13] [59e9c089bdd600b584669dddc48fbcc3] 
- RMPD        [Exercise 1.13] [] [2011-10-11 15:22:50] [a1957df0bc37aec4aa3c994e6a08412c] 
- R           [Survey Scores] [] [2011-10-11 15:27:31] [a1957df0bc37aec4aa3c994e6a08412c] 
- RMPD        [Exercise 1.13] [OpdebeeckMaarten12] [2011-10-11 18:29:02] [df691308a413f42c104a3a322de89bb4] 
-               [Exercise 1.13] [opdebeeckmaarten13] [2011-10-11 18:37:18] [df691308a413f42c104a3a322de89bb4] 
- RM          [Survey Scores] [Task 4: new data] [2011-10-11 18:57:45] [e51846b5e808727784baa8d5c183dcd5] 
- R           [Survey Scores] [Workshop 2 opdrac...] [2011-10-11 22:02:45] [43a0606d8103c0ba382f0586f4417c48] 
- RM          [Survey Scores] [ATTLES Scores] [2011-12-22 15:08:59] [1321c14511baa35aebbc5dda661708fe] 
- R           [Survey Scores] [Survey 2010] [2012-10-04 19:06:57] [0883bf8f4217d775edf6393676d58a73] 
-    D          [Survey Scores] [Resultaten survey...] [2012-10-04 19:09:59] [0883bf8f4217d775edf6393676d58a73] 
- RM          [Survey Scores] [WS2 - taak5b] [2012-10-05 11:06:41] [8ce6c7315af51b5eb6923c5fe455d382] 
- RMPD        [Notched Boxplots] [WS2: Task 6] [2012-10-06 10:14:24] [edf0418499cd31d27dbea8ea1d30b3db] 
- R           [Survey Scores] [Task 5.2] [2012-10-06 11:28:00] [9d6050326bbbd058eed49c2dec5f39c1] 
-               [Survey Scores] [Taak 5] [2012-10-08 19:30:45] [c5e00e3d2459b4cd6380f7873395bbc5] 
- R           [Survey Scores] [Taak 5] [2012-10-08 15:58:52] [c5e00e3d2459b4cd6380f7873395bbc5] 
- R           [Survey Scores] [WS2: Taak 5-2] [2012-10-09 07:38:32] [b43eb6e2e60f3928e6b8367ff6c5b484] 
- RM          [Survey Scores] [connected & separ...] [2012-10-09 08:30:10] [87b90d598c60c012567ac118c8f3a654] 
- RMPD        [Exercise 1.13] [Workshop 2 - Task 2] [2012-10-09 10:57:42] [7073e6f3275d7ce0870c213648af111a] 
- R           [Survey Scores] [workshop 2 Taak 5] [2012-10-09 21:15:38] [081ff4808467d7c84e980fa7f896f721] 
- R           [Survey Scores] [workshop 2 Taak 5...] [2012-10-09 21:27:36] [081ff4808467d7c84e980fa7f896f721] 
- R           [Survey Scores] [Paper 4] [2012-11-30 22:28:17] [f4f48270c576c45d216b84daa061a85b] 
- RMPD        [Exercise 1.13] [Workshop 2 vraag 1] [2013-10-11 12:14:52] [ca911141a7ec8daf372faa3c5d9535e0] 
- RMPD        [Exercise 1.13] [Worshop 2 vraag 3] [2013-10-11 12:34:03] [ca911141a7ec8daf372faa3c5d9535e0] 
- RMP         [Notched Boxplots] [Notched Boxplots ...] [2013-10-12 14:28:22] [74be16979710d4c4e7c6647856088456] 
- R           [Survey Scores] [Connected and sep...] [2013-10-13 14:49:02] [e39a9fdb43d44bc7a3500a1d00251334] 
- RMPD        [Exercise 1.13] [Task 3: Probabili...] [2013-10-14 16:37:09] [e62a289106a5b580d3faaf52f3fb6acb] 
- RM          [Survey Scores] [Workshop 2 - vraag 5] [2013-10-15 08:52:31] [6e6101806504d86600f236fbba4f8aec] 
- R           [Survey Scores] [WS 2 Vraag 5.1] [2013-10-15 09:15:28] [d1af3aceda32c4de5f8ef20fdfdffdc9] 
- RM          [Survey Scores] [Workshop 2 - Task 5] [2013-10-15 12:25:05] [fc82b8c760ed89156a53b254f8e95ae0] 
- RM          [Survey Scores] [Workshop 2 task 5] [2013-10-15 12:46:41] [f12bfb29749f0c3f544bf278d0782c85] 
- RMPD        [Pearson Correlation] [WS2.5a] [2013-10-15 18:48:18] [31634b7e94db88df109226f71dc63e83] 

[Truncated]

Feedback Forum

2010-10-13 16:29:41 [Pascal Wijnen] [reply] 
Daar hier over alle antwoorden te discuteren valt, kunnen we niet echt een goed of fout antwoord geven. Zelf kom ik ook op de gedachte dat er een verschil is tussen de groepen, en dat groep 2 negatiever staat ten opzichte van groep 1. Ook vind ik groep 1 meer connected.

Post a new message

Dataseries X:

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

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'George Udny Yule' @ 72.249.76.132

\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 & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=80353&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=80353&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=80353&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	2 seconds
R Server	'George Udny Yule' @ 72.249.76.132

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	0.97	114	7	0.88	93	7	0.86
2	0.08	55	46	0.09	43	41	0.02
3	0.86	102	7	0.87	83	7	0.84
4	-0.12	34	47	-0.16	27	42	-0.22
5	0.52	76	19	0.6	63	15	0.62
6	0.87	105	9	0.84	86	9	0.81
7	0.75	92	9	0.82	75	8	0.81
8	0.78	95	9	0.83	82	9	0.8
9	-0.66	15	88	-0.71	13	68	-0.68
10	0.92	111	10	0.83	83	9	0.8
11	0.65	85	14	0.72	71	12	0.71
12	0.41	63	18	0.56	59	16	0.57
13	0.47	75	23	0.53	67	21	0.52
14	0.4	70	26	0.46	60	23	0.45
15	0.48	72	19	0.58	65	18	0.57
16	0.21	49	26	0.31	45	23	0.32
17	0.65	82	10	0.78	74	9	0.78
18	0.59	77	12	0.73	71	9	0.78
19	0.34	62	25	0.43	59	25	0.4
20	-0.05	41	46	-0.06	39	41	-0.02

\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 & 0.97 & 114 & 7 & 0.88 & 93 & 7 & 0.86 \tabularnewline
2 & 0.08 & 55 & 46 & 0.09 & 43 & 41 & 0.02 \tabularnewline
3 & 0.86 & 102 & 7 & 0.87 & 83 & 7 & 0.84 \tabularnewline
4 & -0.12 & 34 & 47 & -0.16 & 27 & 42 & -0.22 \tabularnewline
5 & 0.52 & 76 & 19 & 0.6 & 63 & 15 & 0.62 \tabularnewline
6 & 0.87 & 105 & 9 & 0.84 & 86 & 9 & 0.81 \tabularnewline
7 & 0.75 & 92 & 9 & 0.82 & 75 & 8 & 0.81 \tabularnewline
8 & 0.78 & 95 & 9 & 0.83 & 82 & 9 & 0.8 \tabularnewline
9 & -0.66 & 15 & 88 & -0.71 & 13 & 68 & -0.68 \tabularnewline
10 & 0.92 & 111 & 10 & 0.83 & 83 & 9 & 0.8 \tabularnewline
11 & 0.65 & 85 & 14 & 0.72 & 71 & 12 & 0.71 \tabularnewline
12 & 0.41 & 63 & 18 & 0.56 & 59 & 16 & 0.57 \tabularnewline
13 & 0.47 & 75 & 23 & 0.53 & 67 & 21 & 0.52 \tabularnewline
14 & 0.4 & 70 & 26 & 0.46 & 60 & 23 & 0.45 \tabularnewline
15 & 0.48 & 72 & 19 & 0.58 & 65 & 18 & 0.57 \tabularnewline
16 & 0.21 & 49 & 26 & 0.31 & 45 & 23 & 0.32 \tabularnewline
17 & 0.65 & 82 & 10 & 0.78 & 74 & 9 & 0.78 \tabularnewline
18 & 0.59 & 77 & 12 & 0.73 & 71 & 9 & 0.78 \tabularnewline
19 & 0.34 & 62 & 25 & 0.43 & 59 & 25 & 0.4 \tabularnewline
20 & -0.05 & 41 & 46 & -0.06 & 39 & 41 & -0.02 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=80353&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]0.97[/C][C]114[/C][C]7[/C][C]0.88[/C][C]93[/C][C]7[/C][C]0.86[/C][/ROW]
[ROW][C]2[/C][C]0.08[/C][C]55[/C][C]46[/C][C]0.09[/C][C]43[/C][C]41[/C][C]0.02[/C][/ROW]
[ROW][C]3[/C][C]0.86[/C][C]102[/C][C]7[/C][C]0.87[/C][C]83[/C][C]7[/C][C]0.84[/C][/ROW]
[ROW][C]4[/C][C]-0.12[/C][C]34[/C][C]47[/C][C]-0.16[/C][C]27[/C][C]42[/C][C]-0.22[/C][/ROW]
[ROW][C]5[/C][C]0.52[/C][C]76[/C][C]19[/C][C]0.6[/C][C]63[/C][C]15[/C][C]0.62[/C][/ROW]
[ROW][C]6[/C][C]0.87[/C][C]105[/C][C]9[/C][C]0.84[/C][C]86[/C][C]9[/C][C]0.81[/C][/ROW]
[ROW][C]7[/C][C]0.75[/C][C]92[/C][C]9[/C][C]0.82[/C][C]75[/C][C]8[/C][C]0.81[/C][/ROW]
[ROW][C]8[/C][C]0.78[/C][C]95[/C][C]9[/C][C]0.83[/C][C]82[/C][C]9[/C][C]0.8[/C][/ROW]
[ROW][C]9[/C][C]-0.66[/C][C]15[/C][C]88[/C][C]-0.71[/C][C]13[/C][C]68[/C][C]-0.68[/C][/ROW]
[ROW][C]10[/C][C]0.92[/C][C]111[/C][C]10[/C][C]0.83[/C][C]83[/C][C]9[/C][C]0.8[/C][/ROW]
[ROW][C]11[/C][C]0.65[/C][C]85[/C][C]14[/C][C]0.72[/C][C]71[/C][C]12[/C][C]0.71[/C][/ROW]
[ROW][C]12[/C][C]0.41[/C][C]63[/C][C]18[/C][C]0.56[/C][C]59[/C][C]16[/C][C]0.57[/C][/ROW]
[ROW][C]13[/C][C]0.47[/C][C]75[/C][C]23[/C][C]0.53[/C][C]67[/C][C]21[/C][C]0.52[/C][/ROW]
[ROW][C]14[/C][C]0.4[/C][C]70[/C][C]26[/C][C]0.46[/C][C]60[/C][C]23[/C][C]0.45[/C][/ROW]
[ROW][C]15[/C][C]0.48[/C][C]72[/C][C]19[/C][C]0.58[/C][C]65[/C][C]18[/C][C]0.57[/C][/ROW]
[ROW][C]16[/C][C]0.21[/C][C]49[/C][C]26[/C][C]0.31[/C][C]45[/C][C]23[/C][C]0.32[/C][/ROW]
[ROW][C]17[/C][C]0.65[/C][C]82[/C][C]10[/C][C]0.78[/C][C]74[/C][C]9[/C][C]0.78[/C][/ROW]
[ROW][C]18[/C][C]0.59[/C][C]77[/C][C]12[/C][C]0.73[/C][C]71[/C][C]9[/C][C]0.78[/C][/ROW]
[ROW][C]19[/C][C]0.34[/C][C]62[/C][C]25[/C][C]0.43[/C][C]59[/C][C]25[/C][C]0.4[/C][/ROW]
[ROW][C]20[/C][C]-0.05[/C][C]41[/C][C]46[/C][C]-0.06[/C][C]39[/C][C]41[/C][C]-0.02[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=80353&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=80353&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	0.97	114	7	0.88	93	7	0.86
2	0.08	55	46	0.09	43	41	0.02
3	0.86	102	7	0.87	83	7	0.84
4	-0.12	34	47	-0.16	27	42	-0.22
5	0.52	76	19	0.6	63	15	0.62
6	0.87	105	9	0.84	86	9	0.81
7	0.75	92	9	0.82	75	8	0.81
8	0.78	95	9	0.83	82	9	0.8
9	-0.66	15	88	-0.71	13	68	-0.68
10	0.92	111	10	0.83	83	9	0.8
11	0.65	85	14	0.72	71	12	0.71
12	0.41	63	18	0.56	59	16	0.57
13	0.47	75	23	0.53	67	21	0.52
14	0.4	70	26	0.46	60	23	0.45
15	0.48	72	19	0.58	65	18	0.57
16	0.21	49	26	0.31	45	23	0.32
17	0.65	82	10	0.78	74	9	0.78
18	0.59	77	12	0.73	71	9	0.78
19	0.34	62	25	0.43	59	25	0.4
20	-0.05	41	46	-0.06	39	41	-0.02

Pearson correlations of survey scores (and p-values)
	mean	(Ps-Ns)/(Ps+Ns)	(Pc-Nc)/(Pc+Nc)
mean	1 (0)	0.985 (0)	0.977 (0)
(Ps-Ns)/(Ps+Ns)	0.985 (0)	1 (0)	0.997 (0)
(Pc-Nc)/(Pc+Nc)	0.977 (0)	0.997 (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) & 0.985 (0) & 0.977 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.985 (0) & 1 (0) & 0.997 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.977 (0) & 0.997 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=80353&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]0.985 (0)[/C][C]0.977 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.985 (0)[/C][C]1 (0)[/C][C]0.997 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.977 (0)[/C][C]0.997 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=80353&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=80353&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)	0.985 (0)	0.977 (0)
(Ps-Ns)/(Ps+Ns)	0.985 (0)	1 (0)	0.997 (0)
(Pc-Nc)/(Pc+Nc)	0.977 (0)	0.997 (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)	0.942 (0)	0.912 (0)
(Ps-Ns)/(Ps+Ns)	0.942 (0)	1 (0)	0.971 (0)
(Pc-Nc)/(Pc+Nc)	0.912 (0)	0.971 (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) & 0.942 (0) & 0.912 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.942 (0) & 1 (0) & 0.971 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.912 (0) & 0.971 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=80353&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]0.942 (0)[/C][C]0.912 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.942 (0)[/C][C]1 (0)[/C][C]0.971 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.912 (0)[/C][C]0.971 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=80353&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=80353&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)	0.942 (0)	0.912 (0)
(Ps-Ns)/(Ps+Ns)	0.942 (0)	1 (0)	0.971 (0)
(Pc-Nc)/(Pc+Nc)	0.912 (0)	0.971 (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