### Signatures - extended data with combined targets

#### SORTING TABLE DATA: you can sort data either by "Signed" or any % column, each click changes sorting direction. By default, the data is sorted by Target goal %

#### EXPLANATIONS: see below the table.

Country |
Signed |
Target LEVEL 1 |
Target LEVEL 2 |
Target MAIN GOAL |
Target LEVEL 3 |
THRESHOLD (which corresponds to the number of MEPs) |
TARGET MEP - in proportion to the threshold (and MEPs) |
TARGET POP - in proportion to the population |

Min.sig |
Type |
L1% |
Min.sig |
Type |
L2% |
Min.sig |
Type |
G% |
Min.sig |
Type |
L3% |
THR |
% |
MEP |
% |
POP |
% |

The main reason for this representation of sigature statistic is that could be more fair way go get targets during this campaingn. As we know, the national thresholds are corresponding to the numbers of MEP-s which is not represeting the real proportions of population. Small countris are "overpresented" and big countries "underpresented". Therefore, if we think that dividing the number of each country's inhabitants with 447 (1 million signatures is about 1/447 of EU population) will give us a good target then we see that for smaller countries such target is lower than national threshold and for bigger countries it's higher than the target calculated from national threshold.

In this table, all 3 indicators are compared and sorted for each country. So for the smallest EU country, Malta, the lowest target is corresponding to their population and highest is calculated from threshold (therefore corresponds to their number of MEPs). For the biggest country, Germany, the lowest level is the national threshold, then threshold&MEP related target and then population-related one.

As the total of highest levels gives us bigger number than million, the real goal should be somewhere in the middle of 2nd and 3rd level.

#### Calculation for each country: 2levelNational + ((1000000 - 2levelTotal) / (3levelTotal - 2levelTotal)) * (3levelNational - 2levelNational) - and rounded half up

Example for Slovenia: 5640 + ((1000000 - 866754) / (1147223 - 866754)) * (11348 - 5640) = 8351.772666497902 which is 8352 when rounded half up.