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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 13:01:20 +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/t1270472835g8j33hyexeibe23.htm/, Retrieved Thu, 25 Apr 2024 23:22:01 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=74594, Retrieved Thu, 25 Apr 2024 23:22:01 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

319

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] [COLLES] [2010-04-05 13:01:20] [d76b387543b13b5e3afd8ff9e5fdc89f] [Current]

Feedback Forum

2010-04-11 19:29:33 [8326296a4a969e220946fc6855491489] [reply] 
P1 : Relevance In this online unit...-I prefer that   my learning focuses on issues that interest me. 
F1 : Relevance In this online unit...-I found that   my learning focuses on issues that interest me. 
P2 : Relevance In this online unit...-I prefer that   what I learn is important for my professional practice. 
F2 : Relevance In this online unit...-I found that   what I learn is important for my professional practice. 
P3 : Relevance In this online unit...-I prefer that   I learn how to improve my professional practice. 
F3 : Relevance In this online unit...-I found that   I learn how to improve my professional practice. 
P4 : Relevance In this online unit...-I prefer that   what I learn connects well with my professional practice. 
F4 : Relevance In this online unit...-I found that   what I learn connects well with my professional practice. 
P5 : Reflective Thinking In this online unit...-I prefer that   I think critically about how I learn. 
F5 : Reflective Thinking In this online unit...-I found that   I think critically about how I learn. 
P6 : Reflective Thinking In this online unit...-I prefer that   I think critically about my own ideas. 
F6 : Reflective Thinking In this online unit...-I found that   I think critically about my own ideas. 
P7 : Reflective Thinking In this online unit...-I prefer that   I think critically about other students' ideas. 
F7 : Reflective Thinking In this online unit...-I found that   I think critically about other students' ideas. 
P8 : Reflective Thinking In this online unit...-I prefer that   I think critically about ideas in the readings. 
F8 : Reflective Thinking In this online unit...-I found that   I think critically about ideas in the readings. 
P9 : Interactivity In this online unit...-I prefer that   I explain my ideas to other students. 
F9 : Interactivity In this online unit...-I found that   I explain my ideas to other students. 
P10 : Interactivity In this online unit...-I prefer that   I ask other students to explain their ideas. 
F10 : Interactivity In this online unit...-I found that   I ask other students to explain their ideas. 
P11 : Interactivity In this online unit...-I prefer that   other students ask me to explain my ideas. 
F11 : Interactivity In this online unit...-I found that   other students ask me to explain my ideas. 
P12 : Interactivity In this online unit...-I prefer that   other students respond to my ideas. 
F12 : Interactivity In this online unit...-I found that   other students respond to my ideas. 
P13 : Tutor Support In this online unit...-I prefer that   the tutor stimulates my thinking. 
F13 : Tutor Support In this online unit...-I found that   the tutor stimulates my thinking. 
P14 : Tutor Support In this online unit...-I prefer that   the tutor encourages me to participate. 
F14 : Tutor Support In this online unit...-I found that   the tutor encourages me to participate. 
P15 : Tutor Support In this online unit...-I prefer that   the tutor models good discourse. 
F15 : Tutor Support In this online unit...-I found that   the tutor models good discourse. 
P16 : Tutor Support In this online unit...-I prefer that   the tutor models critical self-reflection. 
F16 : Tutor Support In this online unit...-I found that   the tutor models critical self-reflection. 
P17 : Peer Support In this online unit...-I prefer that   other students encourage my participation. 
F17 : Peer Support In this online unit...-I found that   other students encourage my participation. 
P18 : Peer Support In this online unit...-I prefer that   other students praise my contribution. 
F18 : Peer Support In this online unit...-I found that   other students praise my contribution. 
P19 : Peer Support In this online unit...-I prefer that   other students value my contribution. 
F19 : Peer Support In this online unit...-I found that   other students value my contribution. 
P20 : Peer Support In this online unit...-I prefer that   other students empathise with my struggle to learn. 
F20 : Peer Support In this online unit...-I found that   other students empathise with my struggle to learn. 
P21 : Interpretation In this online unit...-I prefer that   I make good sense of other students' messages. 
F21 : Interpretation In this online unit...-I found that   I make good sense of other students' messages. 
P22 : Interpretation In this online unit...-I prefer that   other students make good sense of my messages. 
F22 : Interpretation In this online unit...-I found that   other students make good sense of my messages. 
P23 : Interpretation In this online unit...-I prefer that   I make good sense of the tutor's messages. 
F23 : Interpretation In this online unit...-I found that   I make good sense of the tutor's messages. 
P24 : Interpretation In this online unit...-I prefer that   the tutor makes good sense of my messages. 
F24 : Interpretation In this online unit...-I found that   the tutor makes good sense of my messages. 

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Dataseries X:

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Histogram

Boxplots

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

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	26 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 & 26 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=74594&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]26 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=74594&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=74594&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	26 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	1.03	277	4	0.97	203	3	0.97
2	0.69	192	10	0.9	162	8	0.91
3	1.11	308	12	0.92	216	12	0.89
4	0.64	193	23	0.79	153	22	0.75
5	1.1	293	3	0.98	212	3	0.97
6	0.63	187	20	0.81	158	20	0.78
7	1.01	284	15	0.9	201	13	0.88
8	0.54	172	28	0.72	147	27	0.69
9	0.8	225	11	0.91	175	9	0.9
10	0.59	174	18	0.81	144	16	0.8
11	0.94	262	13	0.91	198	11	0.89
12	0.63	188	22	0.79	156	21	0.76
13	0.87	247	15	0.89	189	12	0.88
14	0.68	200	18	0.83	161	17	0.81
15	0.67	202	24	0.79	162	22	0.76
16	0.42	142	30	0.65	124	26	0.65
17	0.65	196	25	0.77	162	22	0.76
18	0.49	155	26	0.71	135	23	0.71
19	0.66	203	27	0.77	170	22	0.77
20	0.48	168	40	0.62	143	32	0.63
21	0.46	168	45	0.58	130	39	0.54
22	0.22	121	63	0.32	100	53	0.31
23	0.76	223	22	0.82	175	19	0.8
24	0.4	153	46	0.54	130	39	0.54
25	0.97	269	11	0.92	196	9	0.91
26	0.64	198	27	0.76	155	22	0.75
27	0.84	241	17	0.87	180	13	0.87
28	0.77	230	25	0.8	178	22	0.78
29	0.94	261	13	0.91	196	10	0.9
30	0.77	218	15	0.87	175	13	0.86
31	0.82	232	14	0.89	180	13	0.87
32	0.7	204	18	0.84	168	16	0.83
33	0.78	229	23	0.82	172	20	0.79
34	0.39	152	48	0.52	121	41	0.49
35	0.69	207	24	0.79	163	20	0.78
36	0.26	124	54	0.39	109	44	0.42
37	0.85	248	22	0.84	191	20	0.81
38	0.44	160	43	0.58	137	34	0.6
39	0.6	203	43	0.65	155	34	0.64
40	0.22	125	66	0.31	106	50	0.36
41	0.95	258	9	0.93	199	8	0.92
42	0.61	176	15	0.84	153	15	0.82
43	0.94	257	8	0.94	200	7	0.93
44	0.47	145	21	0.75	132	18	0.76
45	1.05	283	6	0.96	210	6	0.94
46	0.74	205	10	0.91	170	9	0.9
47	0.97	263	7	0.95	200	7	0.93
48	0.78	216	10	0.91	176	10	0.89

\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 & 1.03 & 277 & 4 & 0.97 & 203 & 3 & 0.97 \tabularnewline
2 & 0.69 & 192 & 10 & 0.9 & 162 & 8 & 0.91 \tabularnewline
3 & 1.11 & 308 & 12 & 0.92 & 216 & 12 & 0.89 \tabularnewline
4 & 0.64 & 193 & 23 & 0.79 & 153 & 22 & 0.75 \tabularnewline
5 & 1.1 & 293 & 3 & 0.98 & 212 & 3 & 0.97 \tabularnewline
6 & 0.63 & 187 & 20 & 0.81 & 158 & 20 & 0.78 \tabularnewline
7 & 1.01 & 284 & 15 & 0.9 & 201 & 13 & 0.88 \tabularnewline
8 & 0.54 & 172 & 28 & 0.72 & 147 & 27 & 0.69 \tabularnewline
9 & 0.8 & 225 & 11 & 0.91 & 175 & 9 & 0.9 \tabularnewline
10 & 0.59 & 174 & 18 & 0.81 & 144 & 16 & 0.8 \tabularnewline
11 & 0.94 & 262 & 13 & 0.91 & 198 & 11 & 0.89 \tabularnewline
12 & 0.63 & 188 & 22 & 0.79 & 156 & 21 & 0.76 \tabularnewline
13 & 0.87 & 247 & 15 & 0.89 & 189 & 12 & 0.88 \tabularnewline
14 & 0.68 & 200 & 18 & 0.83 & 161 & 17 & 0.81 \tabularnewline
15 & 0.67 & 202 & 24 & 0.79 & 162 & 22 & 0.76 \tabularnewline
16 & 0.42 & 142 & 30 & 0.65 & 124 & 26 & 0.65 \tabularnewline
17 & 0.65 & 196 & 25 & 0.77 & 162 & 22 & 0.76 \tabularnewline
18 & 0.49 & 155 & 26 & 0.71 & 135 & 23 & 0.71 \tabularnewline
19 & 0.66 & 203 & 27 & 0.77 & 170 & 22 & 0.77 \tabularnewline
20 & 0.48 & 168 & 40 & 0.62 & 143 & 32 & 0.63 \tabularnewline
21 & 0.46 & 168 & 45 & 0.58 & 130 & 39 & 0.54 \tabularnewline
22 & 0.22 & 121 & 63 & 0.32 & 100 & 53 & 0.31 \tabularnewline
23 & 0.76 & 223 & 22 & 0.82 & 175 & 19 & 0.8 \tabularnewline
24 & 0.4 & 153 & 46 & 0.54 & 130 & 39 & 0.54 \tabularnewline
25 & 0.97 & 269 & 11 & 0.92 & 196 & 9 & 0.91 \tabularnewline
26 & 0.64 & 198 & 27 & 0.76 & 155 & 22 & 0.75 \tabularnewline
27 & 0.84 & 241 & 17 & 0.87 & 180 & 13 & 0.87 \tabularnewline
28 & 0.77 & 230 & 25 & 0.8 & 178 & 22 & 0.78 \tabularnewline
29 & 0.94 & 261 & 13 & 0.91 & 196 & 10 & 0.9 \tabularnewline
30 & 0.77 & 218 & 15 & 0.87 & 175 & 13 & 0.86 \tabularnewline
31 & 0.82 & 232 & 14 & 0.89 & 180 & 13 & 0.87 \tabularnewline
32 & 0.7 & 204 & 18 & 0.84 & 168 & 16 & 0.83 \tabularnewline
33 & 0.78 & 229 & 23 & 0.82 & 172 & 20 & 0.79 \tabularnewline
34 & 0.39 & 152 & 48 & 0.52 & 121 & 41 & 0.49 \tabularnewline
35 & 0.69 & 207 & 24 & 0.79 & 163 & 20 & 0.78 \tabularnewline
36 & 0.26 & 124 & 54 & 0.39 & 109 & 44 & 0.42 \tabularnewline
37 & 0.85 & 248 & 22 & 0.84 & 191 & 20 & 0.81 \tabularnewline
38 & 0.44 & 160 & 43 & 0.58 & 137 & 34 & 0.6 \tabularnewline
39 & 0.6 & 203 & 43 & 0.65 & 155 & 34 & 0.64 \tabularnewline
40 & 0.22 & 125 & 66 & 0.31 & 106 & 50 & 0.36 \tabularnewline
41 & 0.95 & 258 & 9 & 0.93 & 199 & 8 & 0.92 \tabularnewline
42 & 0.61 & 176 & 15 & 0.84 & 153 & 15 & 0.82 \tabularnewline
43 & 0.94 & 257 & 8 & 0.94 & 200 & 7 & 0.93 \tabularnewline
44 & 0.47 & 145 & 21 & 0.75 & 132 & 18 & 0.76 \tabularnewline
45 & 1.05 & 283 & 6 & 0.96 & 210 & 6 & 0.94 \tabularnewline
46 & 0.74 & 205 & 10 & 0.91 & 170 & 9 & 0.9 \tabularnewline
47 & 0.97 & 263 & 7 & 0.95 & 200 & 7 & 0.93 \tabularnewline
48 & 0.78 & 216 & 10 & 0.91 & 176 & 10 & 0.89 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=74594&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]1.03[/C][C]277[/C][C]4[/C][C]0.97[/C][C]203[/C][C]3[/C][C]0.97[/C][/ROW]
[ROW][C]2[/C][C]0.69[/C][C]192[/C][C]10[/C][C]0.9[/C][C]162[/C][C]8[/C][C]0.91[/C][/ROW]
[ROW][C]3[/C][C]1.11[/C][C]308[/C][C]12[/C][C]0.92[/C][C]216[/C][C]12[/C][C]0.89[/C][/ROW]
[ROW][C]4[/C][C]0.64[/C][C]193[/C][C]23[/C][C]0.79[/C][C]153[/C][C]22[/C][C]0.75[/C][/ROW]
[ROW][C]5[/C][C]1.1[/C][C]293[/C][C]3[/C][C]0.98[/C][C]212[/C][C]3[/C][C]0.97[/C][/ROW]
[ROW][C]6[/C][C]0.63[/C][C]187[/C][C]20[/C][C]0.81[/C][C]158[/C][C]20[/C][C]0.78[/C][/ROW]
[ROW][C]7[/C][C]1.01[/C][C]284[/C][C]15[/C][C]0.9[/C][C]201[/C][C]13[/C][C]0.88[/C][/ROW]
[ROW][C]8[/C][C]0.54[/C][C]172[/C][C]28[/C][C]0.72[/C][C]147[/C][C]27[/C][C]0.69[/C][/ROW]
[ROW][C]9[/C][C]0.8[/C][C]225[/C][C]11[/C][C]0.91[/C][C]175[/C][C]9[/C][C]0.9[/C][/ROW]
[ROW][C]10[/C][C]0.59[/C][C]174[/C][C]18[/C][C]0.81[/C][C]144[/C][C]16[/C][C]0.8[/C][/ROW]
[ROW][C]11[/C][C]0.94[/C][C]262[/C][C]13[/C][C]0.91[/C][C]198[/C][C]11[/C][C]0.89[/C][/ROW]
[ROW][C]12[/C][C]0.63[/C][C]188[/C][C]22[/C][C]0.79[/C][C]156[/C][C]21[/C][C]0.76[/C][/ROW]
[ROW][C]13[/C][C]0.87[/C][C]247[/C][C]15[/C][C]0.89[/C][C]189[/C][C]12[/C][C]0.88[/C][/ROW]
[ROW][C]14[/C][C]0.68[/C][C]200[/C][C]18[/C][C]0.83[/C][C]161[/C][C]17[/C][C]0.81[/C][/ROW]
[ROW][C]15[/C][C]0.67[/C][C]202[/C][C]24[/C][C]0.79[/C][C]162[/C][C]22[/C][C]0.76[/C][/ROW]
[ROW][C]16[/C][C]0.42[/C][C]142[/C][C]30[/C][C]0.65[/C][C]124[/C][C]26[/C][C]0.65[/C][/ROW]
[ROW][C]17[/C][C]0.65[/C][C]196[/C][C]25[/C][C]0.77[/C][C]162[/C][C]22[/C][C]0.76[/C][/ROW]
[ROW][C]18[/C][C]0.49[/C][C]155[/C][C]26[/C][C]0.71[/C][C]135[/C][C]23[/C][C]0.71[/C][/ROW]
[ROW][C]19[/C][C]0.66[/C][C]203[/C][C]27[/C][C]0.77[/C][C]170[/C][C]22[/C][C]0.77[/C][/ROW]
[ROW][C]20[/C][C]0.48[/C][C]168[/C][C]40[/C][C]0.62[/C][C]143[/C][C]32[/C][C]0.63[/C][/ROW]
[ROW][C]21[/C][C]0.46[/C][C]168[/C][C]45[/C][C]0.58[/C][C]130[/C][C]39[/C][C]0.54[/C][/ROW]
[ROW][C]22[/C][C]0.22[/C][C]121[/C][C]63[/C][C]0.32[/C][C]100[/C][C]53[/C][C]0.31[/C][/ROW]
[ROW][C]23[/C][C]0.76[/C][C]223[/C][C]22[/C][C]0.82[/C][C]175[/C][C]19[/C][C]0.8[/C][/ROW]
[ROW][C]24[/C][C]0.4[/C][C]153[/C][C]46[/C][C]0.54[/C][C]130[/C][C]39[/C][C]0.54[/C][/ROW]
[ROW][C]25[/C][C]0.97[/C][C]269[/C][C]11[/C][C]0.92[/C][C]196[/C][C]9[/C][C]0.91[/C][/ROW]
[ROW][C]26[/C][C]0.64[/C][C]198[/C][C]27[/C][C]0.76[/C][C]155[/C][C]22[/C][C]0.75[/C][/ROW]
[ROW][C]27[/C][C]0.84[/C][C]241[/C][C]17[/C][C]0.87[/C][C]180[/C][C]13[/C][C]0.87[/C][/ROW]
[ROW][C]28[/C][C]0.77[/C][C]230[/C][C]25[/C][C]0.8[/C][C]178[/C][C]22[/C][C]0.78[/C][/ROW]
[ROW][C]29[/C][C]0.94[/C][C]261[/C][C]13[/C][C]0.91[/C][C]196[/C][C]10[/C][C]0.9[/C][/ROW]
[ROW][C]30[/C][C]0.77[/C][C]218[/C][C]15[/C][C]0.87[/C][C]175[/C][C]13[/C][C]0.86[/C][/ROW]
[ROW][C]31[/C][C]0.82[/C][C]232[/C][C]14[/C][C]0.89[/C][C]180[/C][C]13[/C][C]0.87[/C][/ROW]
[ROW][C]32[/C][C]0.7[/C][C]204[/C][C]18[/C][C]0.84[/C][C]168[/C][C]16[/C][C]0.83[/C][/ROW]
[ROW][C]33[/C][C]0.78[/C][C]229[/C][C]23[/C][C]0.82[/C][C]172[/C][C]20[/C][C]0.79[/C][/ROW]
[ROW][C]34[/C][C]0.39[/C][C]152[/C][C]48[/C][C]0.52[/C][C]121[/C][C]41[/C][C]0.49[/C][/ROW]
[ROW][C]35[/C][C]0.69[/C][C]207[/C][C]24[/C][C]0.79[/C][C]163[/C][C]20[/C][C]0.78[/C][/ROW]
[ROW][C]36[/C][C]0.26[/C][C]124[/C][C]54[/C][C]0.39[/C][C]109[/C][C]44[/C][C]0.42[/C][/ROW]
[ROW][C]37[/C][C]0.85[/C][C]248[/C][C]22[/C][C]0.84[/C][C]191[/C][C]20[/C][C]0.81[/C][/ROW]
[ROW][C]38[/C][C]0.44[/C][C]160[/C][C]43[/C][C]0.58[/C][C]137[/C][C]34[/C][C]0.6[/C][/ROW]
[ROW][C]39[/C][C]0.6[/C][C]203[/C][C]43[/C][C]0.65[/C][C]155[/C][C]34[/C][C]0.64[/C][/ROW]
[ROW][C]40[/C][C]0.22[/C][C]125[/C][C]66[/C][C]0.31[/C][C]106[/C][C]50[/C][C]0.36[/C][/ROW]
[ROW][C]41[/C][C]0.95[/C][C]258[/C][C]9[/C][C]0.93[/C][C]199[/C][C]8[/C][C]0.92[/C][/ROW]
[ROW][C]42[/C][C]0.61[/C][C]176[/C][C]15[/C][C]0.84[/C][C]153[/C][C]15[/C][C]0.82[/C][/ROW]
[ROW][C]43[/C][C]0.94[/C][C]257[/C][C]8[/C][C]0.94[/C][C]200[/C][C]7[/C][C]0.93[/C][/ROW]
[ROW][C]44[/C][C]0.47[/C][C]145[/C][C]21[/C][C]0.75[/C][C]132[/C][C]18[/C][C]0.76[/C][/ROW]
[ROW][C]45[/C][C]1.05[/C][C]283[/C][C]6[/C][C]0.96[/C][C]210[/C][C]6[/C][C]0.94[/C][/ROW]
[ROW][C]46[/C][C]0.74[/C][C]205[/C][C]10[/C][C]0.91[/C][C]170[/C][C]9[/C][C]0.9[/C][/ROW]
[ROW][C]47[/C][C]0.97[/C][C]263[/C][C]7[/C][C]0.95[/C][C]200[/C][C]7[/C][C]0.93[/C][/ROW]
[ROW][C]48[/C][C]0.78[/C][C]216[/C][C]10[/C][C]0.91[/C][C]176[/C][C]10[/C][C]0.89[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=74594&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=74594&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	1.03	277	4	0.97	203	3	0.97
2	0.69	192	10	0.9	162	8	0.91
3	1.11	308	12	0.92	216	12	0.89
4	0.64	193	23	0.79	153	22	0.75
5	1.1	293	3	0.98	212	3	0.97
6	0.63	187	20	0.81	158	20	0.78
7	1.01	284	15	0.9	201	13	0.88
8	0.54	172	28	0.72	147	27	0.69
9	0.8	225	11	0.91	175	9	0.9
10	0.59	174	18	0.81	144	16	0.8
11	0.94	262	13	0.91	198	11	0.89
12	0.63	188	22	0.79	156	21	0.76
13	0.87	247	15	0.89	189	12	0.88
14	0.68	200	18	0.83	161	17	0.81
15	0.67	202	24	0.79	162	22	0.76
16	0.42	142	30	0.65	124	26	0.65
17	0.65	196	25	0.77	162	22	0.76
18	0.49	155	26	0.71	135	23	0.71
19	0.66	203	27	0.77	170	22	0.77
20	0.48	168	40	0.62	143	32	0.63
21	0.46	168	45	0.58	130	39	0.54
22	0.22	121	63	0.32	100	53	0.31
23	0.76	223	22	0.82	175	19	0.8
24	0.4	153	46	0.54	130	39	0.54
25	0.97	269	11	0.92	196	9	0.91
26	0.64	198	27	0.76	155	22	0.75
27	0.84	241	17	0.87	180	13	0.87
28	0.77	230	25	0.8	178	22	0.78
29	0.94	261	13	0.91	196	10	0.9
30	0.77	218	15	0.87	175	13	0.86
31	0.82	232	14	0.89	180	13	0.87
32	0.7	204	18	0.84	168	16	0.83
33	0.78	229	23	0.82	172	20	0.79
34	0.39	152	48	0.52	121	41	0.49
35	0.69	207	24	0.79	163	20	0.78
36	0.26	124	54	0.39	109	44	0.42
37	0.85	248	22	0.84	191	20	0.81
38	0.44	160	43	0.58	137	34	0.6
39	0.6	203	43	0.65	155	34	0.64
40	0.22	125	66	0.31	106	50	0.36
41	0.95	258	9	0.93	199	8	0.92
42	0.61	176	15	0.84	153	15	0.82
43	0.94	257	8	0.94	200	7	0.93
44	0.47	145	21	0.75	132	18	0.76
45	1.05	283	6	0.96	210	6	0.94
46	0.74	205	10	0.91	170	9	0.9
47	0.97	263	7	0.95	200	7	0.93
48	0.78	216	10	0.91	176	10	0.89

Pearson correlations of survey scores (and p-values)
	mean	(Ps-Ns)/(Ps+Ns)	(Pc-Nc)/(Pc+Nc)
mean	1 (0)	0.911 (0)	0.907 (0)
(Ps-Ns)/(Ps+Ns)	0.911 (0)	1 (0)	0.995 (0)
(Pc-Nc)/(Pc+Nc)	0.907 (0)	0.995 (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) & 0.911 (0) & 0.907 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.911 (0) & 1 (0) & 0.995 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.907 (0) & 0.995 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=74594&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]0.911 (0)[/C][C]0.907 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.911 (0)[/C][C]1 (0)[/C][C]0.995 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.907 (0)[/C][C]0.995 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=74594&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=74594&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)	0.911 (0)	0.907 (0)
(Ps-Ns)/(Ps+Ns)	0.911 (0)	1 (0)	0.995 (0)
(Pc-Nc)/(Pc+Nc)	0.907 (0)	0.995 (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)	0.805 (0)	0.773 (0)
(Ps-Ns)/(Ps+Ns)	0.805 (0)	1 (0)	0.948 (0)
(Pc-Nc)/(Pc+Nc)	0.773 (0)	0.948 (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) & 0.805 (0) & 0.773 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.805 (0) & 1 (0) & 0.948 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.773 (0) & 0.948 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=74594&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]0.805 (0)[/C][C]0.773 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.805 (0)[/C][C]1 (0)[/C][C]0.948 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.773 (0)[/C][C]0.948 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=74594&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=74594&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)	0.805 (0)	0.773 (0)
(Ps-Ns)/(Ps+Ns)	0.805 (0)	1 (0)	0.948 (0)
(Pc-Nc)/(Pc+Nc)	0.773 (0)	0.948 (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