Martin Kuna is so kind to help me as a consultant on my diss work and he started with a simple questions:

#### 1. What is the surface actually collected (in sight of one collector * number of collectors) for every polygon?

Lets presume that collector (picker) is visually controlling a strip of 1 m width in front of him. Knowing the polygon dimensions I could easily calculate what surface was actually seen. Surprisingly it is not so few – I calculated all 373 polygons and got:

average seen surface is 13.2%, median 12.5%, min 9.45% and max 17.5% of the whole surface. By multiplication of finds number/weight I could asses amount of finds present on actual surface.

#### 2. If there is a 1 piece of pottery, what is the probability to find it? And 2, 3, 4 pieces…?

Probability of 1 piece is given by percentage of cover (e.g. around 12/13%). Consequently I could multiplicate this percentage if more sherds are on the surface…

#### 3. Repeating the collection in next season, what is a probability the pottery comes from the same source (one collection)?

Hm, this could not be calculated or stated per se. The only guideline would be a pottery dating – if it is of the same age (e.g. late neolithic), I could assume of the same origin (e.g. one neolithic pit). But nothing guarantees this and this is a weak point.

#### 4. Under the rule You have two assemblages from different sampling seasons originating from one source (e.g. that neolithic pit), You could calculate the independent conditions influencing the visibility (differencies in field surface visibility, etc…).

Well, this could be the core of my work. It means to:

a) find the polygons with the narrow-dated assemblage in several consequent seasons

b) compare the amount of samples

c) get the preliminary “visibility” coefficients

d) try to calculate what influences this visibility

e) test the result on a different polygons/different material from the same polygon

Hey Good hearsay ! an likeableoffers

To processed click on the constituent substandard of

https://drive.google.com/file/d/1U_pL5rCgOUjT9_62AEEiL7RuNNJLQb3s/preview