Using Friedman Test For Creating Comparable Group Results Of Non Parametric Innovation Competence Data
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The document discusses the use of the Friedman test for analyzing non-parametric data related to innovation competence among individuals, highlighting the challenges of evaluating linguistic and non-numeric responses. It emphasizes the importance of emotional intelligence in distinguishing successful leaders and companies, and describes a self-evaluation method using linguistic statements. Despite the inherent limitations of linguistic data, the Friedman test is presented as a reliable statistical method for comparing group results, aiding in the analysis of creative competencies within organizations.
Using Friedman Test For Creating Comparable Group Results Of Non Parametric Innovation Competence Data
- 1. 1 Using Friedman test for creating comparable group results of non- parametric innovation competence data Pasi Porkka, M.Sc. Jari Jussila, M.Sc. Anu Suominen, M.Sc. Tampere University of Technology, Pori Unit 4.11.2012 Industrial Management and Engineering
- 2. Outline • Research on human beings and their behavior • Specific features of nonnumeric and nonparametric data • Studied Innovation competence data • The Friedman test • Results • Discussion Industrial Management and Engineering
- 3. Research on human beings and their behavior • Some studied aspects are nonnumeric • Linguistic: questionnaires, evaluations and interviews • can be described in words but not measured with parameters: • related to feelings, needs, wishes or relations between humans Industrial Management and Engineering
- 4. Specific features of nonnumeric and nonparametric data • Parametrical = there is an implicit functional relationship between different answers => comparable • Problems of nonparametric data: • comparison of results of two different people difficult • achieving reliable group results • traditional statistical methods are mathematically and statistically hardly ever valid to such data ”Quite strong” + ”Strong” = ? • When humans evaluate something, the inherent method is linguistic • linguistic variables are nonparametric by nature and therefore not comparable • Yet, numbers are easier to store into computers • For nonparametric data, statistically valid methods are nonparametric Industrial Management and Engineering
- 5. 5 Motivation to study competences • Studies have shown that IQ over 120 does not anymore differentiate creative from the less creative (Csikszentmihalyi 1996) • Emotional intelligence makes up for 80-90 percent of the competences that differentiate successful leaders from average leaders (Goleman, Boyatzis, McKee 2002) • The emotional intelligence is what makes the difference between successful and average companies (Kets de Vries 2006) 4.11.2012 Industrial Management and Engineering
- 6. Individual’s innovation competence 6 (iceberg model, Spencer and Spencer 1993; Kets de Vries 2001) Skills (Spencer and Spencer 1993) Knowledge (Spencer and Spencer 1993) Self-concept, Attitudes (Spencer and Spencer 1993) Traits (Spencer and Spencer 1993) Motives (Spencer and Spencer 1993) Emotions (Kets de Vries 2001) Defenses (Kets de Vries 2001) 4.11.2012 Industrial Management and Engineering
- 7. Self-evaluation • Several statements to each competence (totally 77) • Linguistic statements evaluated with linguistic answers, which are transformed into numbers. • Values are given to current and future state • Future – current = creative tension (by Senge) • Answers to statements related to one competence are summed (with fuzzy logic) together to gain a single value for a competence • Each respondent has his/hers own scale of degree → answers of different respondents are not comparable Industrial Management and Engineering
- 8. 8 Self-evaluation as method SELF-EVALUATION with linguistic statements with nominal scale I use theories and models for s a ll e w s a s w oll a ht o b n oit a zi n a g r o si h T d e zili vi c a ni et a b e d ot el p o e p s e g a r u o c n e explaining complicated issues .r e n n a m 1 e e r g a yl g n o rt S e er g A for both Current: 0,755 current and Saved to database Target: 0,865 e e r g a si D future states in numeric form Creat.tens: 0,110 e e r g a si d yl g n o rt S 0 Notice! Data is still nonparametric t e gr a T t n err u C t e gr a T t n err u C Industrial Management and Engineering 4.11.2012
- 9. 9 Self-evaluation data The data collected with linguistic variables is by nature weakest in the statistical sense. 1. Measurable only with nominal scale 2. Personal scale of degree (results of different answerers not comparable) Values are used merely as means of separating the properties of elements into different classes. With nominal scale, traditional statistical methods (sums, correlations, etc.) are not applicable. • Own scale of degree and variables are related→ answers of one respondent are comparable • Answers of one respondent can be ranked 4.11.2012 Industrial Management and Engineering
- 10. The Friedman test: example Actual numeric values Variables Respondent Strength of Strength of father mother A 0,2 0,1 B 0,3 0,3 C 0,2 0,1 D 0,3 0,2 E 0,3 0,9 SUMS 1,3 1,6 Industrial Management and Engineering
- 11. The Friedman test: example Numeric values transformed into rankings Respondent Strength of Strength of father mother A 2 1 B 1,5 1,5 C 2 1 D 2 1 E 1 2 SUMS 8,5 6,5 Industrial Management and Engineering
- 12. Benefits for using Friedman test • Removes the personal scale of degrees, since actual given values are turned into rankings • Sums the rankings - statistically valid group results • Results comparable to other groups (companies) • Possible to calculate the minimum difference value, within which the values are considered equal → great help in analysis • Minimum difference depends on amount of respondents, the distribution of answers → is different in every group and has to be calculated separately Industrial Management and Engineering
- 13. Averages of creative tensions of two different companies A n=12 B n=10 Averages of creative tensions of two capacity 0,26 Self-control 0,31 Absorptive different companies 0,25 Absorptive capacity 0,28 Professional and technical expertise 0,23 Change orientation 0,27 Self-confidence 0,22 Analytical thinking 0,27 Intuitive thinking 0,21 Conceptual thinking 0,26 Understanding others 0,20 Understanding others 0,24 Analytical thinking 0,17 Self-development 0,22 Communication 0,16 Flexibility 0,21 Accurate self-assessment 0,16 Stress tolerance 0,20 Conceptual thinking 0,15 Professional and technical expertise 0,20 Self-control 0,15 Trustworthiness 0,19 Self-development 0,13 Intuitive thinking 0,19 Flexibility 0,13 Conflict management 0,18 Stress tolerance 0,12 Seeking information 0,15 Relationship building 0,11 Relationship building 0,14 Initiative 0,11 Achievement orientation 0,13 Leveraging diversity 0,11 Accurate self-assessment 0,12 Imagination 0,10 Independence 0,11 Seeking information 0,10 Teamwork and cooperation 0,11 Change orientation 0,09 Self-confidence 0,09 Conflict management 0,08 Divergent thinking 0,09 Teamwork and cooperation 0,08 Responsibility 0,08 Trustworthiness 0,08 Initiative 0,07 Achievement orientation 0,07 Imagination 0,06 Responsibility 0,06 Leveraging diversity 0,05 Divergent thinking 0,04 Communication 0,04 Independence 0,02 Risk orientation 0,00 Risk orientation 3,56 Management and Engineering Industrial SUM 4,25 SUM
- 14. Rankings of creative tensions of two different companies A n=12, α=0.05, min.diff. 5,71 B n=10, α=0.05, min.diff 5,79 21,83 Self-control 21,70 Absorptive capacity 20,83 Absorptive capacity 21,20 Intuitive thinking 20,25 Change orientation 21,10 Professional and technical expertise 19,17 Conceptual thinking 19,50 Self-confidence 18,83 Analytical thinking 19,30 Understanding others 18,08 Understanding others 18,30 Communication 17,50 Stress tolerance 18,10 Analytical thinking 16,63 Flexibility 17,80 Accurate self-assessment 15,67 Trustworthiness 16,80 Flexibility 15,67 Self-development 16,70 Self-development 14,92 Professional and technical expertise 16,40 Self-control 14,83 Conflict management 16,05 Stress tolerance 14,63 Intuitive thinking 16,00 Conceptual thinking 13,00 Relationship building 14,40 Relationship building 12,29 Seeking information 13,90 Initiative 12,13 Teamwork and cooperation 11,80 Leveraging diversity 11,79 Achievement orientation 11,20 Conflict management 11,63 Accurate self-assessment 11,15 Seeking information 11,46 Self-confidence 10,85 Change orientation 11,29 Divergent thinking 10,70 Imagination 11,17 Initiative 10,15 Responsibility 10,67 Imagination 9,00 Teamwork and cooperation 10,00 Independence 8,30 Achievement orientation 9,88 Responsibility 8,15 Trustworthiness 8,83 Leveraging diversity 7,90 Divergent thinking 7,79 Risk orientation 7,05 Independence 7,25 Communication 4,50 Risk orientation 378,00 SUM Industrial Management and Engineering 378,00 SUM
- 15. Results Out of the total number of 27 competencies, in both organizations there are • 7 corresponding competencies clustered with the high ranked creative tensions • 6 corresponding competencies clustered with the low ranked creative tensions • The further analysis of the meaning of the similarities in the clusters remains to be done in the future. • Significance of the Friedmann test: 1. allows this further analysis to be carried out in the first place. => Otherwise sheer speculation and conjecture 2. Friedman test can be carried out to a rather small group of respondents; however, naturally the group results more reliable the greater the respondent group is. Industrial Management and Engineering
- 16. Conclusion • Group results of linguistic data produced with self- evaluation, although raising questions of invalidity by its nature can be analyzed with statistically valid method of Friedman test in order to compare those group results • However, the further analysis of the gathered results, the meaning of the clustered rankings, still have to carried out by a human Industrial Management and Engineering
- 17. Discussion Why to use the Friedman test? • Right (statistically) results in analysis with ALL possible answers • Minimum difference great help in analysis • Results comparable with other groups Why NOT to use? • Almost the same results as with the (old) summing style • Have to learn new method Industrial Management and Engineering
- 18. 18 Thank You for your attention 4.11.2012 Industrial Management and Engineering
- 19. 19 Contact details Porkka, Pasi Tampere University of Technology/ Pori E-mail: pasi.porkka(at)tut.fi Jussila, Jari Tampere University of Technology/ Pori E-mail: jari.j.jussila(at)tut.fi Suominen, Anu Tampere University of Technology/ Pori E-mail: anu.suominen(at)tut.fi 4.11.2012 Industrial Management and Engineering