# Poorly Transported -- An Analysis

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**Note:** You can expand areas that look like this:

:::spoiler

Courtesy of "Sanna Marin Reaction Stickers" on Telegram

:::

## Introduction

As cities grow and evolve, public transport needs to do the same in order to offer people good connections between their work, their home, and leasure activity places. Depending on the political situation though, one may think, that the Quality of public transport may vary a lot between different districts, favoring different neighbourhoods depending on the current government. We therefore decided to measure the quality of the Public Transport for different neighbourhoods and assess, whether e.g. the income has a decisive impact on how good the quality actually is.

## Map

To get a general impression on the Quality of the Public Transport, the following maps show the Transport Qualities for each neighbourhood as well as the average and mean income. Layers can be switched using the button at the top-right. It is also possible to see the different underlying polygons that we used to assess the quality.

<iframe src="https://gereondusella.de/map_quality.html" style="width: 100%; height: 800px"> Your Browser does not support iFrames.</iframe>

Link to the map (70MB): [https://gereondusella.de/map_quality.html](https://gereondusella.de/map_quality.html)
Another map which includes the distance polygons (200MB): [https://gereondusella.de/map_both_simple_with_distance.html](https://gereondusella.de/map_both_simple_with_distance.html)

## Static Analysis

For our static analysis, we focus on the income as well as the age group per neighbourhood.

### Transport Quality and Income

<!-- Quality by municipality -->

<!-- Quality by median income -->

<!-- Quality by average income -->

::: spoiler Result for the above regression analysis:
- slope: [[-0.00031198]]
- Mean squared error: 157.47
- Coefficient of determination: 0.05

:::

#### Analysis

We can see, that the income is not a good predictor on whether an area has good Public Transport or not. Therefore, a direct link between public transport quality and income is not suggested

:::spoiler **Income Group Analysis**

**Low Income Group**

<!-- Quality by low income group -->
Residents belonging to the low income group earn up to 13 287 euros annually.
Result for the above regression analysis:
- slope: [[0.46481026]]
- Mean squared error: 161.74
- Coefficient of determination: 0.03

---

**Medium Income Group**

<!-- Quality by middle income group -->
Residents belonging to the middle income group earn 13 288 - 31 873 euros annually.
Result for the above regression analysis:
- slope: [[0.30174997]]
- Mean squared error: 156.87
- Coefficient of determination: 0.05

---

**High Income Group**

<!-- Quality by high income group -->
Residents belonging to the high income group earn over 31 874 euros annually.
Result for the above regression analysis:
- slope: [[-0.3337255]]
- Mean squared error: 154.01
- Coefficient of determination: 0.07

:::

### Transport Quality Histograms

<!-- Quality histogram all -->

:::spoiler **Histograms by weekday | weekend and daytime**

<!-- Quality histogram weekday -->

<!-- Quality histogram weekend -->

<!-- Quality histogram day time -->

<!-- Quality histogram night time -->

:::

#### Analysis

Public Transport in the Helsinki Metropolitain Area in general seems to be quite good, as it follows a normal distribution. It is interesting to note, that the quality does not reduce significantly at weekends win comparison to weekdays, though the same cannot be said for the night times.

### Age Group Analysis

<!-- Quality correlation by age groups -->

:::spoiler **Regression analysis of Age Groups**

<!-- Regression analysis age 25 to 29 -->
Result for the above regression analysis:
- slope: [[1.63939058]]
- Mean squared error: 122.42
- Coefficient of determination: 0.26

---

<!-- Regression analysis age 30 to 34 -->
Result for the above regression analysis:
- slope: [[2.49699493]]
- Mean squared error: 122.15
- Coefficient of determination: 0.26

:::

#### Analysis

Looking at the correlation coefficients between different age groups and the Public Transport Quality, it is interesting to see, that especially people between Age 20 -- 34 tend to live in areas with a good public transport quality. An explanation for this could be, that people in this age class tend to live in rented flats, which, due to their higher population density, and tend to be served better by public transport. This explanation fits also to the decline fromage 0 to 7, as especially young families tend to move to the suburbs, where population density is lower, thus leading to a worse quality of public transport. Quality increases again after the age of 65, as older people tend to live in care homes again, which in turn have higher population densities.

## Conclusion

We could not find any clear relationship between the income and transport quality but we still made some interesting findings. Certain age groups have some correlation to transport quality when the data is analyzed by postcode areas. Especially the age groups from 20 to 34 correlate with the transport quality by a fair amount. Because of the presumably tight interlocks between transport quality and population density, taking the latter into account should be an interesting target for a further analysis.