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 = 0.033

Ikke normal distribution af Spearman r = 0.0013

Vis kun resultater > r = 0.033

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 0.0558	Svag positiv 0.0311	Svag negativ -0.0169	Svag positiv 0.0917	Svag positiv 0.0304	Svag negativ -0.0128	Svag negativ -0.1541
Answer 2	-	Svag positiv 0.0229	Svag negativ -0.0006	Svag negativ -0.0443	Svag positiv 0.0632	Svag positiv 0.0453	Svag positiv 0.0130	Svag negativ -0.0942
Answer 3	-	Svag negativ -0.0032	Svag negativ -0.0122	Svag negativ -0.0413	Svag negativ -0.0464	Svag positiv 0.0469	Svag positiv 0.0786	Svag negativ -0.0196
Answer 4	-	Svag positiv 0.0437	Svag positiv 0.0345	Svag negativ -0.0196	Svag positiv 0.0152	Svag positiv 0.0307	Svag positiv 0.0204	Svag negativ -0.0981
Answer 5	-	Svag positiv 0.0303	Svag positiv 0.1280	Svag positiv 0.0134	Svag positiv 0.0733	Svag negativ -0.0005	Svag negativ -0.0203	Svag negativ -0.1759
Answer 6	-	Svag negativ -0.0003	Svag positiv 0.0082	Svag negativ -0.0630	Svag negativ -0.0082	Svag positiv 0.0195	Svag positiv 0.0830	Svag negativ -0.0315
Answer 7	-	Svag positiv 0.0124	Svag positiv 0.0382	Svag negativ -0.0694	Svag negativ -0.0241	Svag positiv 0.0473	Svag positiv 0.0641	Svag negativ -0.0514
Answer 8	-	Svag positiv 0.0696	Svag positiv 0.0850	Svag negativ -0.0333	Svag positiv 0.0150	Svag positiv 0.0346	Svag positiv 0.0134	Svag negativ -0.1364
Answer 9	-	Svag positiv 0.0667	Svag positiv 0.1676	Svag positiv 0.0077	Svag positiv 0.0694	Svag negativ -0.0128	Svag negativ -0.0517	Svag negativ -0.1817
Answer 10	-	Svag positiv 0.0780	Svag positiv 0.0754	Svag negativ -0.0211	Svag positiv 0.0249	Svag positiv 0.0347	Svag negativ -0.0132	Svag negativ -0.1303
Answer 11	-	Svag positiv 0.0579	Svag positiv 0.0528	Svag negativ -0.0090	Svag positiv 0.0083	Svag positiv 0.0201	Svag positiv 0.0308	Svag negativ -0.1198
Answer 12	-	Svag positiv 0.0389	Svag positiv 0.1036	Svag negativ -0.0362	Svag positiv 0.0359	Svag positiv 0.0255	Svag positiv 0.0297	Svag negativ -0.1521
Answer 13	-	Svag positiv 0.0645	Svag positiv 0.1041	Svag negativ -0.0438	Svag positiv 0.0262	Svag positiv 0.0423	Svag positiv 0.0174	Svag negativ -0.1603
Answer 14	-	Svag positiv 0.0710	Svag positiv 0.1022	Svag negativ -0.0015	Svag negativ -0.0085	Svag negativ -0.0006	Svag positiv 0.0087	Svag negativ -0.1169
Answer 15	-	Svag positiv 0.0555	Svag positiv 0.1365	Svag negativ -0.0429	Svag positiv 0.0179	Svag negativ -0.0158	Svag positiv 0.0223	Svag negativ -0.1178
Answer 16	-	Svag positiv 0.0591	Svag positiv 0.0271	Svag negativ -0.0384	Svag negativ -0.0401	Svag positiv 0.0655	Svag positiv 0.0283	Svag negativ -0.0709

Eksport til MS Excel

Denne funktionalitet vil være tilgængelig i dine egne VUCA-afstemninger

Okay

2023.11.22

Valerii Kosenko

Produktejer SaaS Pet Project SDTest®

Valerii blev kvalificeret som social pædagoge-psykolog i 1993 og har siden anvendt sin viden inden for projektledelse.
Valerii opnåede en kandidatgrad og projekt- og programlederkvalifikationen i 2013. Under sin kandidatuddannelse blev han fortrolig med Project Roadmap (GPM Deutsche Gesellschaft für Projektmanagement E. V.) og spiraldynamik.
Valerii tog forskellige spiraldynamikforsøg og brugte sin viden og erfaring til at tilpasse den aktuelle version af SDTest.
Valerii er forfatteren af at udforske usikkerheden i V.U.C.A. Koncept ved hjælp af spiraldynamik og matematisk statistik inden for psykologi, mere end 20 internationale afstemninger.

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