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 0.0548	Svag positiv 0.0285	Svag negativ -0.0173	Svag positiv 0.0940	Svag positiv 0.0358	Svag negativ -0.0156	Svag negativ -0.1560
Answer 2	-	Svag positiv 0.0192	Svag negativ -0.0048	Svag negativ -0.0394	Svag positiv 0.0659	Svag positiv 0.0491	Svag positiv 0.0117	Svag negativ -0.0981
Answer 3	-	Svag negativ -0.0003	Svag negativ -0.0088	Svag negativ -0.0450	Svag negativ -0.0440	Svag positiv 0.0471	Svag positiv 0.0739	Svag negativ -0.0191
Answer 4	-	Svag positiv 0.0429	Svag positiv 0.0271	Svag negativ -0.0230	Svag positiv 0.0182	Svag positiv 0.0351	Svag positiv 0.0239	Svag negativ -0.0995
Answer 5	-	Svag positiv 0.0273	Svag positiv 0.1298	Svag positiv 0.0101	Svag positiv 0.0772	Svag negativ -0.0006	Svag negativ -0.0183	Svag negativ -0.1784
Answer 6	-	Svag negativ -0.0026	Svag positiv 0.0050	Svag negativ -0.0621	Svag negativ -0.0081	Svag positiv 0.0240	Svag positiv 0.0856	Svag negativ -0.0346
Answer 7	-	Svag positiv 0.0105	Svag positiv 0.0339	Svag negativ -0.0661	Svag negativ -0.0304	Svag positiv 0.0517	Svag positiv 0.0686	Svag negativ -0.0515
Answer 8	-	Svag positiv 0.0635	Svag positiv 0.0732	Svag negativ -0.0275	Svag positiv 0.0143	Svag positiv 0.0370	Svag positiv 0.0172	Svag negativ -0.1336
Answer 9	-	Svag positiv 0.0734	Svag positiv 0.1618	Svag positiv 0.0069	Svag positiv 0.0644	Svag negativ -0.0109	Svag negativ -0.0489	Svag negativ -0.1811
Answer 10	-	Svag positiv 0.0764	Svag positiv 0.0679	Svag negativ -0.0139	Svag positiv 0.0290	Svag positiv 0.0338	Svag negativ -0.0123	Svag negativ -0.1342
Answer 11	-	Svag positiv 0.0634	Svag positiv 0.0535	Svag negativ -0.0091	Svag positiv 0.0113	Svag positiv 0.0238	Svag positiv 0.0247	Svag negativ -0.1260
Answer 12	-	Svag positiv 0.0449	Svag positiv 0.0941	Svag negativ -0.0341	Svag positiv 0.0342	Svag positiv 0.0332	Svag positiv 0.0255	Svag negativ -0.1534
Answer 13	-	Svag positiv 0.0691	Svag positiv 0.0966	Svag negativ -0.0393	Svag positiv 0.0295	Svag positiv 0.0417	Svag positiv 0.0148	Svag negativ -0.1626
Answer 14	-	Svag positiv 0.0775	Svag positiv 0.0903	Svag negativ -0.0019	Svag negativ -0.0089	Svag positiv 0.0048	Svag positiv 0.0140	Svag negativ -0.1223
Answer 15	-	Svag positiv 0.0544	Svag positiv 0.1280	Svag negativ -0.0345	Svag positiv 0.0152	Svag negativ -0.0178	Svag positiv 0.0236	Svag negativ -0.1158
Answer 16	-	Svag positiv 0.0703	Svag positiv 0.0262	Svag negativ -0.0371	Svag negativ -0.0377	Svag positiv 0.0697	Svag positiv 0.0204	Svag negativ -0.0788

Eksport til MS Excel

Denne funktionalitet vil være tilgængelig i dine egne VUCA-afstemninger

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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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