– according to the value of feature x 4 , i.e. expenditure on culture. It also scored relatively high in the category relating to the number of cultural institutions (3rd place in the country). The next place was taken by the Zachodniopomorskie Voivodship, mainly due to the income obtained from the cultural sector per capita . The third place was taken by the Dolnośląskie Voivodship, which achieved relatively good results according to all analysed characteristics.
The second class was created by five voivodships: Podkarpackie, Podlaskie, Śląskie, Mazowieckie and Kujawsko
Michal Klobučník CDFMR, Martin Plešivčák CDFMR and Milan Vrábeľ CDFMR
Rc ls = club rank in league l in season s
Cc s = country coefficient in season s (according to UEFA)
In the first place, we had to take into account the fact that the number of clubs is different in individual leagues, and the number of clubs sometimes changed during the seasons. Winning in a league of 12 teams (for example, the Scottish League in 2016/2017) is not as difficult as in a league of 20 teams (e.g. the English Premier League in 2016/2017). Each club in a particular league gained a score according to the position in that season. To take
Agata Frankowska CDFMR, Izabella Łęcka CDFMR and Jan Frankowski CDFMR
Most of the NGO leaders were not present on social media. The most active individuals were: Wojciech Wilk of the Polish Center for International Aid and Janina Ochojska of Polish Humanitarian Action. The former gained the highest score in terms of LinkedIn presence, and the latter on Twitter. These two leaders have years of field experience in the area of development and humanitarian assistance, as well as established contacts with international organisations. The leaders of religious organisations tended to ignore Twitter and Linked-In.
.g. near Kościelna Street) were also assessed to be negative (over 60% negative or neutral characteristics). It is important to note that the average values of the quality indicator (between 20% and 60% negative and neutral characteristics) are typical of the majority of the public spaces analysed. These mainly include city-centre marketplaces (including, in particular, the Old Square), some parks (e.g. Maciejewski Park) and squares (e.g. Kazimierz Nowakowski Square or Wolności Square). Spaces with average scores are distributed across various parts of the analysed area
structured into three sectors, namely: the Supreme People’s Procuratorate (SPP) responsible for handling and preventing cases of embezzlement and bribery, the Central Commission for Disciplinary Inspection (CCDI) to check corruption among political elites, and the Ministry of Supervision (MOS) to restrain corruption and maladministration within the civil service ( Keyuan, 2003 ; UNDP, 1999; Glynn et al ., 1997).
Corruption Perception Index (CPI), Corruption Control and Government Efficiency in Percentile Rank and Governance Score
Mazozo N. Mahlangu DFMR and Jennifer M. Fitchett CDMR
Fouriesburg, Free State
30 September 2017
Overcast with thunder: threat of rain, followed by “quick shower” and sunshine
Johannesburg Garden Venue
Mountain View, Gauteng
12 December 2017
Warm ”sunny” summer temperatures (29°C): “a perfect summers day”
PE Inland Island
Plettenberg Western Cape Bay,
27 February 2010
When asked about the importance of hosting their wedding in a natural setting, each respondent scored higher than seven on a score out of ten as portrayed in Figure 2 . In this regards, a natural setting
Agnieszka Szczepańska CDFMR and Katarzyna Pietrzyk CDFPMR
expressed by the mean of the scores given by the entire surveyed population, as well as by different age and sex groups to accentuate the differences in the opinions of male, female, older and younger respondents. None of the evaluated public spaces received an average of 5 points. Public spaces 3, 5, 8, 9, 14, 17 and 19 were most highly evaluated, which is consistent with the results of the multidimensional analysis of spatial order in public spaces 3, 5, 9, 17 and 19, but not in public spaces 8 and 14. The respondents gave the lowest marks to public spaces 2, 4, 7, 10
Iwona Murawska, Beata Przyborowska, Violetta Kopińska and Piotr Błajet
are divided into the types indicated in Table 2 . (3)
Kujawsko-Pomorskie Voivodeship. Education compared to place of residence
Secondary and vocational
Source: http://www.polskawliczbach.pl/kujawsko_pomorskie (2017.09.05)
School type based on the EVA index
Average scores + average effectiveness
Low scores + high effectiveness
Ali Soltani, Rasoul Balaghi Inaloo, Mohammad Rezaei, Fatemeh Shaer and M. Akbari Riyabi
itself gives a score of 1 (equivalent priority). Therefore, 1 is assigned to all elements on the diagonal of the pair-wise comparison matrix ( Mahmoodzadeh, 2010 : 92).
B. Calculation of criteria weighting: This stage includes the following operations: a) adding up the values of each column of the pair-wise comparison matrix; b) dividing each element of the matrix by its column total (the resulting matrix is called normalised pair-wise comparison matrix); (c) computing the average of the elements in each row of the normalised matrix. These averages will give an
household’s score, where assets that are more unequally distributed will have a higher weight. The relative ranking of households using their scores is then used as a measure of SES ( Filmer and Pritchett, 2001 ).
However, PCA is designed to be used on continuous, normally-distributed data and so its application to data sets that contain categorical variables, as is often the case with census data, is considered to be inappropriate ( Booysen et al., 2008 ; Howe et al., 2008 ). Multiple Correspondence Analysis (MCA) is more appropriate, as it is the only multivariate