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 0.0544	Svag positiv 0.0285	Svag negativ -0.0171	Svag positiv 0.0941	Svag positiv 0.0361	Svag negativ -0.0163	Svag negativ -0.1557
Answer 2	-	Svag positiv 0.0202	Svag negativ -0.0049	Svag negativ -0.0399	Svag positiv 0.0657	Svag positiv 0.0500	Svag positiv 0.0112	Svag negativ -0.0986
Answer 3	-	Svag positiv 0.0004	Svag negativ -0.0089	Svag negativ -0.0451	Svag negativ -0.0446	Svag positiv 0.0491	Svag positiv 0.0744	Svag negativ -0.0211
Answer 4	-	Svag positiv 0.0418	Svag positiv 0.0272	Svag negativ -0.0238	Svag positiv 0.0179	Svag positiv 0.0370	Svag positiv 0.0237	Svag negativ -0.0996
Answer 5	-	Svag positiv 0.0276	Svag positiv 0.1291	Svag positiv 0.0104	Svag positiv 0.0764	Svag positiv 0.0022	Svag negativ -0.0189	Svag negativ -0.1798
Answer 6	-	Svag negativ -0.0014	Svag positiv 0.0052	Svag negativ -0.0624	Svag negativ -0.0092	Svag positiv 0.0258	Svag positiv 0.0856	Svag negativ -0.0361
Answer 7	-	Svag positiv 0.0118	Svag positiv 0.0341	Svag negativ -0.0666	Svag negativ -0.0312	Svag positiv 0.0535	Svag positiv 0.0684	Svag negativ -0.0530
Answer 8	-	Svag positiv 0.0644	Svag positiv 0.0725	Svag negativ -0.0276	Svag positiv 0.0142	Svag positiv 0.0396	Svag positiv 0.0161	Svag negativ -0.1352
Answer 9	-	Svag positiv 0.0746	Svag positiv 0.1608	Svag positiv 0.0067	Svag positiv 0.0637	Svag negativ -0.0075	Svag negativ -0.0496	Svag negativ -0.1829
Answer 10	-	Svag positiv 0.0759	Svag positiv 0.0673	Svag negativ -0.0125	Svag positiv 0.0284	Svag positiv 0.0351	Svag negativ -0.0124	Svag negativ -0.1350
Answer 11	-	Svag positiv 0.0636	Svag positiv 0.0529	Svag negativ -0.0083	Svag positiv 0.0105	Svag positiv 0.0258	Svag positiv 0.0243	Svag negativ -0.1273
Answer 12	-	Svag positiv 0.0448	Svag positiv 0.0943	Svag negativ -0.0337	Svag positiv 0.0335	Svag positiv 0.0351	Svag positiv 0.0250	Svag negativ -0.1545
Answer 13	-	Svag positiv 0.0718	Svag positiv 0.0955	Svag negativ -0.0386	Svag positiv 0.0291	Svag positiv 0.0438	Svag positiv 0.0135	Svag negativ -0.1647
Answer 14	-	Svag positiv 0.0797	Svag positiv 0.0903	Svag negativ -0.0024	Svag negativ -0.0095	Svag positiv 0.0070	Svag positiv 0.0126	Svag negativ -0.1236
Answer 15	-	Svag positiv 0.0548	Svag positiv 0.1271	Svag negativ -0.0342	Svag positiv 0.0132	Svag negativ -0.0139	Svag positiv 0.0231	Svag negativ -0.1170
Answer 16	-	Svag positiv 0.0722	Svag positiv 0.0248	Svag negativ -0.0364	Svag negativ -0.0393	Svag positiv 0.0740	Svag positiv 0.0176	Svag negativ -0.0799

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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