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 = 0.0318

Ikke normal distribution af Spearman r = 0.0013

Vis kun resultater > r = 0.0318

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 0.0526	Svag positiv 0.0260	Svag negativ -0.0183	Svag positiv 0.0946	Svag positiv 0.0358	Svag negativ -0.0143	Svag negativ -0.1540
Answer 2	-	Svag positiv 0.0175	Svag negativ -0.0058	Svag negativ -0.0388	Svag positiv 0.0668	Svag positiv 0.0496	Svag positiv 0.0117	Svag negativ -0.0970
Answer 3	-	Svag negativ -0.0035	Svag negativ -0.0091	Svag negativ -0.0441	Svag negativ -0.0435	Svag positiv 0.0478	Svag positiv 0.0747	Svag negativ -0.0200
Answer 4	-	Svag positiv 0.0414	Svag positiv 0.0257	Svag negativ -0.0232	Svag positiv 0.0188	Svag positiv 0.0356	Svag positiv 0.0249	Svag negativ -0.0993
Answer 5	-	Svag positiv 0.0226	Svag positiv 0.1270	Svag positiv 0.0111	Svag positiv 0.0773	Svag negativ -0.0008	Svag negativ -0.0177	Svag negativ -0.1772
Answer 6	-	Svag negativ -0.0057	Svag positiv 0.0040	Svag negativ -0.0620	Svag negativ -0.0076	Svag positiv 0.0246	Svag positiv 0.0860	Svag negativ -0.0351
Answer 7	-	Svag positiv 0.0082	Svag positiv 0.0329	Svag negativ -0.0653	Svag negativ -0.0294	Svag positiv 0.0519	Svag positiv 0.0693	Svag negativ -0.0520
Answer 8	-	Svag positiv 0.0627	Svag positiv 0.0709	Svag negativ -0.0265	Svag positiv 0.0134	Svag positiv 0.0376	Svag positiv 0.0181	Svag negativ -0.1337
Answer 9	-	Svag positiv 0.0710	Svag positiv 0.1600	Svag positiv 0.0074	Svag positiv 0.0646	Svag negativ -0.0109	Svag negativ -0.0487	Svag negativ -0.1817
Answer 10	-	Svag positiv 0.0739	Svag positiv 0.0654	Svag negativ -0.0147	Svag positiv 0.0296	Svag positiv 0.0318	Svag negativ -0.0126	Svag negativ -0.1357
Answer 11	-	Svag positiv 0.0627	Svag positiv 0.0522	Svag negativ -0.0096	Svag positiv 0.0108	Svag positiv 0.0250	Svag positiv 0.0244	Svag negativ -0.1268
Answer 12	-	Svag positiv 0.0431	Svag positiv 0.0920	Svag negativ -0.0336	Svag positiv 0.0339	Svag positiv 0.0327	Svag positiv 0.0254	Svag negativ -0.1537
Answer 13	-	Svag positiv 0.0685	Svag positiv 0.0956	Svag negativ -0.0394	Svag positiv 0.0308	Svag positiv 0.0405	Svag positiv 0.0148	Svag negativ -0.1628
Answer 14	-	Svag positiv 0.0779	Svag positiv 0.0883	Svag negativ -0.0001	Svag negativ -0.0092	Svag positiv 0.0046	Svag positiv 0.0135	Svag negativ -0.1225
Answer 15	-	Svag positiv 0.0537	Svag positiv 0.1267	Svag negativ -0.0337	Svag positiv 0.0152	Svag negativ -0.0175	Svag positiv 0.0234	Svag negativ -0.1158
Answer 16	-	Svag positiv 0.0689	Svag positiv 0.0247	Svag negativ -0.0371	Svag negativ -0.0383	Svag positiv 0.0702	Svag positiv 0.0203	Svag negativ -0.0791

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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