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 = 0.0329

Ikke normal distribution af Spearman r = 0.0013

Vis kun resultater > r = 0.0329

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 0.0566	Svag positiv 0.0332	Svag negativ -0.0170	Svag positiv 0.0912	Svag positiv 0.0308	Svag negativ -0.0153	Svag negativ -0.1537
Answer 2	-	Svag positiv 0.0223	Svag positiv 0.0011	Svag negativ -0.0442	Svag positiv 0.0639	Svag positiv 0.0464	Svag positiv 0.0120	Svag negativ -0.0960
Answer 3	-	Svag negativ -0.0031	Svag negativ -0.0104	Svag negativ -0.0407	Svag negativ -0.0463	Svag positiv 0.0475	Svag positiv 0.0779	Svag negativ -0.0213
Answer 4	-	Svag positiv 0.0437	Svag positiv 0.0357	Svag negativ -0.0197	Svag positiv 0.0161	Svag positiv 0.0311	Svag positiv 0.0187	Svag negativ -0.0987
Answer 5	-	Svag positiv 0.0296	Svag positiv 0.1300	Svag positiv 0.0124	Svag positiv 0.0749	Svag positiv 0.0014	Svag negativ -0.0231	Svag negativ -0.1771
Answer 6	-	Svag negativ -0.0008	Svag positiv 0.0090	Svag negativ -0.0613	Svag negativ -0.0070	Svag positiv 0.0196	Svag positiv 0.0803	Svag negativ -0.0321
Answer 7	-	Svag positiv 0.0118	Svag positiv 0.0401	Svag negativ -0.0693	Svag negativ -0.0246	Svag positiv 0.0471	Svag positiv 0.0623	Svag negativ -0.0505
Answer 8	-	Svag positiv 0.0697	Svag positiv 0.0875	Svag negativ -0.0316	Svag positiv 0.0155	Svag positiv 0.0346	Svag positiv 0.0098	Svag negativ -0.1373
Answer 9	-	Svag positiv 0.0679	Svag positiv 0.1707	Svag positiv 0.0105	Svag positiv 0.0676	Svag negativ -0.0138	Svag negativ -0.0545	Svag negativ -0.1821
Answer 10	-	Svag positiv 0.0793	Svag positiv 0.0772	Svag negativ -0.0208	Svag positiv 0.0242	Svag positiv 0.0343	Svag negativ -0.0152	Svag negativ -0.1300
Answer 11	-	Svag positiv 0.0590	Svag positiv 0.0559	Svag negativ -0.0071	Svag positiv 0.0082	Svag positiv 0.0205	Svag positiv 0.0266	Svag negativ -0.1213
Answer 12	-	Svag positiv 0.0405	Svag positiv 0.1050	Svag negativ -0.0363	Svag positiv 0.0361	Svag positiv 0.0253	Svag positiv 0.0277	Svag negativ -0.1522
Answer 13	-	Svag positiv 0.0655	Svag positiv 0.1056	Svag negativ -0.0439	Svag positiv 0.0270	Svag positiv 0.0417	Svag positiv 0.0152	Svag negativ -0.1601
Answer 14	-	Svag positiv 0.0728	Svag positiv 0.1049	Svag negativ -0.0002	Svag negativ -0.0088	Svag negativ -0.0007	Svag positiv 0.0061	Svag negativ -0.1187
Answer 15	-	Svag positiv 0.0561	Svag positiv 0.1378	Svag negativ -0.0415	Svag positiv 0.0178	Svag negativ -0.0162	Svag positiv 0.0194	Svag negativ -0.1176
Answer 16	-	Svag positiv 0.0606	Svag positiv 0.0308	Svag negativ -0.0348	Svag negativ -0.0421	Svag positiv 0.0642	Svag positiv 0.0250	Svag negativ -0.0717

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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