Bei dieser Übung ging es darum die Bodenpreise einer selbst gewählten Gemeinde in Rheinland-Pfalz zuerst in Google Earth darzustellen und anschließend eine statistische Auswertung durchzuführen.
1.) Darstellung mit Google Earth
Die Aufgabe war es die verschiedenen Bereich mit Polygonen in Google Earth abzugrenzen und ihrem Bodenpreis nach einzufärben und groß zu machen (1€/m² = 1m). Die Datengrundlage kam vom Bodenrichtwertinformationssystem (BORIS) Rheinland-Pfalz. Die dort erzeugten Karten habe ich als Screenshot gespeichert und als Bild-Overlay in Google Earth eingefügt.
Anhand dieser Vorlage war es mir möglich die einzelnen Gebiete mit Polygonen nachzufahren und sie anschließend einzufärben und die richtige Größe zu geben. Außerdem habe ich sie nur zu 50% deckend gemacht, sodass es möglich ist zu erkennen, wo die jeweiligen Bodenpreise sind.
had to that a legend be created so that you can assign the color values. I have also sorted in the kmz file, the land prices for clarity.
second Statistical analysis
In the statistical analysis, I first created the original list and out of a stem-leaf plot with the corresponding answers.
example, land prices
as church: Kaiserslautern
original list (n = 32): 160 / 140 / 140 / 165 / 175 / 180 / 175 / 190 / 210 / 260 / 170 / 210 / 255 / 170 / 190 / 490 / 660 / 360 / 370 / 1200 / 1000 / 600 / 180 / 1400 / 340 / 190 / 215 / 360 / 400 / 270 / 170 / 220
If you turn this diagram 90 degrees to get a bar chart showing the distribution shows better.
It can now make statistical analysis easy:
minimum: 140 maximum
: 1400
span: 1260
mode: 170, 190
Median: 212.5 Mean
: 350.46875
Außreiser: 1400 , 1200, 1000
Analysis:
Land prices in the study area with 1260 have a very large range. This is due to the difference of the maximum with the minimum, in this case 1400 € / m² - 140 € / m². The average value is formed in the dividing the sum of all values of n. He is in the area studied € 350.46875 / m². The median is the value at which 50% of values higher and 50% of the values are lower than him. Since n = 32 is there is the mode from the average of the two middle values (210 € / m² and 215 € / m²). The mode is the value that occurs most often. In this particular example, there are the floor Price 170 € / m² and 190 € / m², which occur 3 times each. Due to the described values, Mode and arithmetic means, it stands to reason that the three largest values 1000 € / m², 1200 € / m² and 1,400 € / m² Außreiser, as these are well above average and far away from the remaining values. A possible explanation for the significantly higher values of which has the high values are next to each other (see Google Earth) and thus form a district with a similar price range. The situation of high prices is centrally located in Kaiserslautern and are thus probably the most sought after and therefore the most expensive. Also striking is that the prices decrease from the center.
positional and scattering parameters:
location parameter will describe the values of the sample elements with respect to the measurement scale,
the totality of values. location parameters are considered:
- Arithmetic mean
- Quantile
-
mode - geometric mean
- Harmonic mean
scattering parameter analysis of the distribution of measured values. These include:
- variance
- Wingspan
- Mean absolute deviation
- average quartile range
Here is the kmz file and the textual version in pdf format for download in a zip file.
positional and scattering parameters:
location parameter will describe the values of the sample elements with respect to the measurement scale,
the totality of values. location parameters are considered:
- Arithmetic mean
- Quantile
-
mode - geometric mean
- Harmonic mean
scattering parameter analysis of the distribution of measured values. These include:
- variance
- Wingspan
- Mean absolute deviation
- average quartile range
Here is the kmz file and the textual version in pdf format for download in a zip file.
