Demographic questions were transformed for the sake of the calculation of the correct statistics; their names were, respectively, changed. Below we list the types of changes in variables and their names.

1) Some of the questions were transformed for the sake of the calculation of the correct statistics; their names were, respectively, changed. Below we list the types of changes in variables and their names. Some questions that can be defined as nominal scale were recoded into the series of 1/0 variables, that show the percentage of voices given for an option. This recoding was done to the following variables of the datasets; the new names are presented below.

2) When transforming variables p162-169 we obtained 40 new variables. In a sake of convenience we present the new names at the bottom of the text; because of the same reason variables movaspil are located at the end of the list of the variables DMHRU.

3) Most of the variables represent the so called ordinal scales: they express the intensity of an attitude on the scales starting from 1-3 to 1-11. They are illustrated with the help of average. In that cases where the highest value in the questionnaire is ascribed to an option Difficult to say it was declared as missing.

4) In the case of the question, which concerns the visiting of monuments. we produce both types of variables – ordinal, which is represented by an average, and nominal (1/0) represented by percentage. The frequency of visiting (1-4. never to many times) could be considered conditionally as a scale and average can be calculated, but the safer way is to consider the distribution of the every option separately (% of those who never visited) which is done with the help of variables monuments… .

5) In the case of variable 66, evaluation of religions we left variable as it is for the calculation of average, but at the end of the data set we added variables p66.1-p66.12 which measures those who gave whatever attitude versus those who never heard about such religion, the awareness about the religion which is also important.

6) In a case of the 44 variables about the number of the books read, we left variable as it is. However, as it is not advisable to calculate an average from the grouped/ interval scale, we added variable knygyp133, which shows the number of respondents who read at least 6 books versus those who read less, as it is more correct way of presentation.

7) In some cases new variable was produced:

Dochod – income per capita
IPIW – inversely proportional index of wealth which can be used as a substitute for material situation of a family
Urban – showing only urban population versus rural.

8) Several indices were produced using the batteries of the questions which were purported to measure some well known construct and placed at the bottom of the list. This is done for the sake of reduction of the information and illustration of many questions at once. These indices, which are the sums of answers to the questions divided by the number of the questions, were calculated only on the variables that show high intercorrelation, or in statistical terms showed high factor loadings and high percentage of the explained variability. The indices are named by the concept what is supposedly lies behind several individual variables and the figures in brackets present the number of the question in the questionnaries of 2013 and 2015 (in brackets).