The Tale of the Tall Oak

Once upon a time, there was a tiny oak tree sapling named Peety. Peety dreamed of growing up into a mighty oak tree.

Each year, Peety grew a little bit taller. He stretched his branches toward the sun and felt his trunk thicken as he grew.

Over many years, Peety grew from a sapling into a young tree and finally into a tall, mature oak! He was so tall that he could see over the whole forest.

Peety noticed that the other tall oak trees had thick trunks, too. His friend Paul reached high into the sky just like Peety. Paul's trunk was thick and sturdy at the base.

The small saplings that were sprouting had skinny little trunks. But Peety knew that would change over time as they grew taller.

Peety realized that, just like him, the taller an oak tree was, the thicker its trunk became.

So even though the forest was filled with all different sizes of oak trees, Peety noticed a pattern - a correlation between tree height and trunk width. The tall trees always had thicker trunks, while the small saplings had skinny trunks. This was how pine trees grew strong enough to reach great heights!

If you record how a tree grows - its height and trunk thickness - and plot it on a picture or graph, then the correlation is when these two things change together. That is, if you see that one is increasing, the other is also increasing, and vice versa.

The SDTEST^® gives clues to someone's motivational values. However, additional polls can provide more pieces of the puzzle.

Imagine also giving a "Fears" poll. It asks people to rate different fears from 0 (not scary) to 5 (very scary).

Now imagine 100 people who took both tests. You could match up each person's SDTEST^® colors with their rated fears.

If people high in Blue values feared uncertainty more, that insight ties values to perceptions. Blue people may resist change more.

Or if Orange achievers feared failure most, that reveals their drive. They may overwork to avoid mistakes.

Comparing tests gives an expanded picture of values in action. More puzzle pieces make the whole image more apparent!

Multiple tests can work together, like colors blending on a palette. Other polls reveal what engages your values, like how your hobbies show what activities you enjoy most. Combined, they paint a richer picture of what motivates our thoughts and deeds.

Below you can read an abridged version of the results of our VUCA poll “Fears“. The full results of our VUCA poll “Fears“ are available for free in the FAQ section after login or registration.

Frygt.

Diagrammer Korrelation

VUCA

Kritisk værdi af korrelationskoefficienten

Normal distribution af William Sealy Gosset (studerende) r = 0.0316

Ikke normal distribution af Spearman r = 0.0013

Vis kun resultater > r = 0.0316

Fordeling	Ikke normal	Ikke normal	Ikke normal	Normal	Normal	Normal	Normal	Normal
Alle spørgsmål Alle spørgsmål Min største frygt er
Min største frygt er
Answer 1	-	Svag positiv 0.0522	Svag positiv 0.0266	Svag negativ -0.0186	Svag positiv 0.0954	Svag positiv 0.0378	Svag negativ -0.0168	Svag negativ -0.1547
Answer 2	-	Svag positiv 0.0173	Svag negativ -0.0066	Svag negativ -0.0372	Svag positiv 0.0650	Svag positiv 0.0505	Svag positiv 0.0113	Svag negativ -0.0964
Answer 3	-	Svag negativ -0.0023	Svag negativ -0.0098	Svag negativ -0.0447	Svag negativ -0.0435	Svag positiv 0.0498	Svag positiv 0.0760	Svag negativ -0.0228
Answer 4	-	Svag positiv 0.0429	Svag positiv 0.0285	Svag negativ -0.0236	Svag positiv 0.0178	Svag positiv 0.0370	Svag positiv 0.0239	Svag negativ -0.1014
Answer 5	-	Svag positiv 0.0236	Svag positiv 0.1255	Svag positiv 0.0115	Svag positiv 0.0748	Svag negativ -0.0003	Svag negativ -0.0158	Svag negativ -0.1766
Answer 6	-	Svag negativ -0.0021	Svag positiv 0.0035	Svag negativ -0.0610	Svag negativ -0.0089	Svag positiv 0.0258	Svag positiv 0.0859	Svag negativ -0.0377
Answer 7	-	Svag positiv 0.0108	Svag positiv 0.0322	Svag negativ -0.0653	Svag negativ -0.0290	Svag positiv 0.0523	Svag positiv 0.0697	Svag negativ -0.0542
Answer 8	-	Svag positiv 0.0654	Svag positiv 0.0697	Svag negativ -0.0253	Svag positiv 0.0132	Svag positiv 0.0387	Svag positiv 0.0170	Svag negativ -0.1355
Answer 9	-	Svag positiv 0.0739	Svag positiv 0.1594	Svag positiv 0.0062	Svag positiv 0.0625	Svag negativ -0.0068	Svag negativ -0.0485	Svag negativ -0.1841
Answer 10	-	Svag positiv 0.0754	Svag positiv 0.0637	Svag negativ -0.0140	Svag positiv 0.0278	Svag positiv 0.0330	Svag negativ -0.0118	Svag negativ -0.1362
Answer 11	-	Svag positiv 0.0630	Svag positiv 0.0502	Svag negativ -0.0081	Svag positiv 0.0099	Svag positiv 0.0272	Svag positiv 0.0253	Svag negativ -0.1287
Answer 12	-	Svag positiv 0.0436	Svag positiv 0.0894	Svag negativ -0.0329	Svag positiv 0.0311	Svag positiv 0.0345	Svag positiv 0.0281	Svag negativ -0.1537
Answer 13	-	Svag positiv 0.0710	Svag positiv 0.0924	Svag negativ -0.0396	Svag positiv 0.0292	Svag positiv 0.0439	Svag positiv 0.0164	Svag negativ -0.1649
Answer 14	-	Svag positiv 0.0815	Svag positiv 0.0874	Svag negativ -0.0024	Svag negativ -0.0121	Svag positiv 0.0062	Svag positiv 0.0139	Svag negativ -0.1211
Answer 15	-	Svag positiv 0.0553	Svag positiv 0.1244	Svag negativ -0.0332	Svag positiv 0.0121	Svag negativ -0.0145	Svag positiv 0.0246	Svag negativ -0.1163
Answer 16	-	Svag positiv 0.0717	Svag positiv 0.0218	Svag negativ -0.0381	Svag negativ -0.0388	Svag positiv 0.0734	Svag positiv 0.0173	Svag negativ -0.0782

Eksport til MS Excel

Denne funktionalitet vil være tilgængelig i dine egne VUCA-afstemninger

Okay

2023.11.22

Valerii Kosenko

Produktejer SaaS SDTEST®

Valerii blev uddannet socialpædagog-psykolog i 1993 og har siden anvendt sin viden i projektledelse.
Valerii opnåede en kandidatgrad og projekt- og programlederkvalifikationen i 2013. I løbet af sin kandidatuddannelse blev han fortrolig med Project Roadmap (GPM Deutsche Gesellschaft für Projektmanagement e. V.) og Spiral Dynamics.
Valerii er forfatteren til at udforske usikkerheden i V.U.C.A. koncept ved hjælp af Spiral Dynamics og matematisk statistik i psykologi, og 38 internationale meningsmålinger.

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