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 = 0.0322

Ikke normal distribution af Spearman r = 0.0013

Vis kun resultater > r = 0.0322

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 0.0482	Svag positiv 0.0333	Svag negativ -0.0178	Svag positiv 0.0944	Svag positiv 0.0354	Svag negativ -0.0171	Svag negativ -0.1538
Answer 2	-	Svag positiv 0.0174	Svag positiv 0.0011	Svag negativ -0.0402	Svag positiv 0.0648	Svag positiv 0.0458	Svag positiv 0.0125	Svag negativ -0.0960
Answer 3	-	Svag negativ -0.0041	Svag negativ -0.0091	Svag negativ -0.0457	Svag negativ -0.0452	Svag positiv 0.0480	Svag positiv 0.0760	Svag negativ -0.0179
Answer 4	-	Svag positiv 0.0395	Svag positiv 0.0308	Svag negativ -0.0225	Svag positiv 0.0193	Svag positiv 0.0305	Svag positiv 0.0233	Svag negativ -0.0963
Answer 5	-	Svag positiv 0.0251	Svag positiv 0.1311	Svag positiv 0.0097	Svag positiv 0.0793	Svag negativ -0.0013	Svag negativ -0.0223	Svag negativ -0.1782
Answer 6	-	Svag negativ -0.0063	Svag positiv 0.0106	Svag negativ -0.0658	Svag negativ -0.0081	Svag positiv 0.0208	Svag positiv 0.0844	Svag negativ -0.0308
Answer 7	-	Svag positiv 0.0102	Svag positiv 0.0417	Svag negativ -0.0701	Svag negativ -0.0279	Svag positiv 0.0479	Svag positiv 0.0660	Svag negativ -0.0502
Answer 8	-	Svag positiv 0.0636	Svag positiv 0.0810	Svag negativ -0.0282	Svag positiv 0.0139	Svag positiv 0.0352	Svag positiv 0.0140	Svag negativ -0.1346
Answer 9	-	Svag positiv 0.0657	Svag positiv 0.1683	Svag positiv 0.0050	Svag positiv 0.0671	Svag negativ -0.0147	Svag negativ -0.0505	Svag negativ -0.1789
Answer 10	-	Svag positiv 0.0751	Svag positiv 0.0714	Svag negativ -0.0215	Svag positiv 0.0267	Svag positiv 0.0290	Svag negativ -0.0113	Svag negativ -0.1304
Answer 11	-	Svag positiv 0.0615	Svag positiv 0.0584	Svag negativ -0.0058	Svag positiv 0.0074	Svag positiv 0.0185	Svag positiv 0.0234	Svag negativ -0.1234
Answer 12	-	Svag positiv 0.0410	Svag positiv 0.0994	Svag negativ -0.0346	Svag positiv 0.0348	Svag positiv 0.0296	Svag positiv 0.0233	Svag negativ -0.1529
Answer 13	-	Svag positiv 0.0660	Svag positiv 0.1017	Svag negativ -0.0382	Svag positiv 0.0281	Svag positiv 0.0398	Svag positiv 0.0139	Svag negativ -0.1626
Answer 14	-	Svag positiv 0.0718	Svag positiv 0.0982	Svag negativ -0.0017	Svag negativ -0.0070	Svag positiv 0.0024	Svag positiv 0.0108	Svag negativ -0.1221
Answer 15	-	Svag positiv 0.0549	Svag positiv 0.1333	Svag negativ -0.0333	Svag positiv 0.0169	Svag negativ -0.0197	Svag positiv 0.0204	Svag negativ -0.1180
Answer 16	-	Svag positiv 0.0657	Svag positiv 0.0273	Svag negativ -0.0343	Svag negativ -0.0433	Svag positiv 0.0646	Svag positiv 0.0246	Svag negativ -0.0750

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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